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Volume 139: International Conference on Machine Learning, 18-24 July 2021, Virtual

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Editors: Marina Meila, Tong Zhang

[bib][citeproc]

A New Representation of Successor Features for Transfer across Dissimilar Environments

Majid Abdolshah, Hung Le, Thommen Karimpanal George, Sunil Gupta, Santu Rana, Svetha Venkatesh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1-9

Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling

Kuruge Darshana Abeyrathna, Bimal Bhattarai, Morten Goodwin, Saeed Rahimi Gorji, Ole-Christoffer Granmo, Lei Jiao, Rupsa Saha, Rohan K. Yadav; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10-20

Debiasing Model Updates for Improving Personalized Federated Training

Durmus Alp Emre Acar, Yue Zhao, Ruizhao Zhu, Ramon Matas, Matthew Mattina, Paul Whatmough, Venkatesh Saligrama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:21-31

Memory Efficient Online Meta Learning

Durmus Alp Emre Acar, Ruizhao Zhu, Venkatesh Saligrama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:32-42

Robust Testing and Estimation under Manipulation Attacks

Jayadev Acharya, Ziteng Sun, Huanyu Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:43-53

GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning

Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:54-65

f-Domain Adversarial Learning: Theory and Algorithms

David Acuna, Guojun Zhang, Marc T. Law, Sanja Fidler; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:66-75

Towards Rigorous Interpretations: a Formalisation of Feature Attribution

Darius Afchar, Vincent Guigue, Romain Hennequin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:76-86

Acceleration via Fractal Learning Rate Schedules

Naman Agarwal, Surbhi Goel, Cyril Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:87-99

A Regret Minimization Approach to Iterative Learning Control

Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:100-109

Towards the Unification and Robustness of Perturbation and Gradient Based Explanations

Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, Himabindu Lakkaraju; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:110-119

Label Inference Attacks from Log-loss Scores

Abhinav Aggarwal, Shiva Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:120-129

Deep kernel processes

Laurence Aitchison, Adam Yang, Sebastian W. Ober; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:130-140

How Does Loss Function Affect Generalization Performance of Deep Learning? Application to Human Age Estimation

Ali Akbari, Muhammad Awais, Manijeh Bashar, Josef Kittler; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:141-151

On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting

Shunta Akiyama, Taiji Suzuki; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:152-162

Slot Machines: Discovering Winning Combinations of Random Weights in Neural Networks

Maxwell M Aladago, Lorenzo Torresani; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:163-174

A large-scale benchmark for few-shot program induction and synthesis

Ferran Alet, Javier Lopez-Contreras, James Koppel, Maxwell Nye, Armando Solar-Lezama, Tomas Lozano-Perez, Leslie Kaelbling, Joshua Tenenbaum; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:175-186

Robust Pure Exploration in Linear Bandits with Limited Budget

Ayya Alieva, Ashok Cutkosky, Abhimanyu Das; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:187-195

Communication-Efficient Distributed Optimization with Quantized Preconditioners

Foivos Alimisis, Peter Davies, Dan Alistarh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:196-206

Non-Exponentially Weighted Aggregation: Regret Bounds for Unbounded Loss Functions

Pierre Alquier; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:207-218

Dataset Dynamics via Gradient Flows in Probability Space

David Alvarez-Melis, Nicolò Fusi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:219-230

Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive Complexity

Georgios Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Alberto Marchetti-Spaccamela, Rebecca Reiffenhäuser; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:231-242

Safe Reinforcement Learning with Linear Function Approximation

Sanae Amani, Christos Thrampoulidis, Lin Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:243-253

Automatic variational inference with cascading flows

Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:254-263

Sparse Bayesian Learning via Stepwise Regression

Sebastian E. Ament, Carla P. Gomes; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:264-274

Locally Persistent Exploration in Continuous Control Tasks with Sparse Rewards

Susan Amin, Maziar Gomrokchi, Hossein Aboutalebi, Harsh Satija, Doina Precup; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:275-285

Preferential Temporal Difference Learning

Nishanth V. Anand, Doina Precup; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:286-296

Unitary Branching Programs: Learnability and Lower Bounds

Fidel Ernesto Diaz Andino, Maria Kokkou, Mateus De Oliveira Oliveira, Farhad Vadiee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:297-306

The Logical Options Framework

Brandon Araki, Xiao Li, Kiran Vodrahalli, Jonathan Decastro, Micah Fry, Daniela Rus; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:307-317

Annealed Flow Transport Monte Carlo

Michael Arbel, Alex Matthews, Arnaud Doucet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:318-330

Permutation Weighting

David Arbour, Drew Dimmery, Arjun Sondhi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:331-341

Analyzing the tree-layer structure of Deep Forests

Ludovic Arnould, Claire Boyer, Erwan Scornet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:342-350

Dropout: Explicit Forms and Capacity Control

Raman Arora, Peter Bartlett, Poorya Mianjy, Nathan Srebro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:351-361

Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients

Artem Artemev, David R. Burt, Mark van der Wilk; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:362-372

Deciding What to Learn: A Rate-Distortion Approach

Dilip Arumugam, Benjamin Van Roy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:373-382

Private Adaptive Gradient Methods for Convex Optimization

Hilal Asi, John Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:383-392

Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry

Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:393-403

Combinatorial Blocking Bandits with Stochastic Delays

Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu, Constantine Caramanis, Sanjay Shakkottai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:404-413

Dichotomous Optimistic Search to Quantify Human Perception

Julien Audiffren; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:414-424

Federated Learning under Arbitrary Communication Patterns

Dmitrii Avdiukhin, Shiva Kasiviswanathan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:425-435

Asynchronous Distributed Learning : Adapting to Gradient Delays without Prior Knowledge

Rotem Zamir Aviv, Ido Hakimi, Assaf Schuster, Kfir Yehuda Levy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:436-445

Decomposable Submodular Function Minimization via Maximum Flow

Kyriakos Axiotis, Adam Karczmarz, Anish Mukherjee, Piotr Sankowski, Adrian Vladu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:446-456

Differentially Private Query Release Through Adaptive Projection

Sergul Aydore, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Ankit A. Siva; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:457-467

On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent

Shahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake E Woodworth, Nathan Srebro, Amir Globerson, Daniel Soudry; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:468-477

On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification

Zahra Babaiee, Ramin Hasani, Mathias Lechner, Daniela Rus, Radu Grosu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:478-489

Uniform Convergence, Adversarial Spheres and a Simple Remedy

Gregor Bachmann, Seyed-Mohsen Moosavi-Dezfooli, Thomas Hofmann; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:490-499

Faster Kernel Matrix Algebra via Density Estimation

Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:500-510

Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees

Kishan Panaganti Badrinath, Dileep Kalathil; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:511-520

Skill Discovery for Exploration and Planning using Deep Skill Graphs

Akhil Bagaria, Jason K Senthil, George Konidaris; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:521-531

Locally Adaptive Label Smoothing Improves Predictive Churn

Dara Bahri, Heinrich Jiang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:532-542

How Important is the Train-Validation Split in Meta-Learning?

Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason Lee, Sham Kakade, Huan Wang, Caiming Xiong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:543-553

Stabilizing Equilibrium Models by Jacobian Regularization

Shaojie Bai, Vladlen Koltun, Zico Kolter; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:554-565

Don’t Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification

Yu Bai, Song Mei, Huan Wang, Caiming Xiong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:566-576

Principled Exploration via Optimistic Bootstrapping and Backward Induction

Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu, Zhaoran Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:577-587

GLSearch: Maximum Common Subgraph Detection via Learning to Search

Yunsheng Bai, Derek Xu, Yizhou Sun, Wei Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:588-598

Breaking the Limits of Message Passing Graph Neural Networks

Muhammet Balcilar, Pierre Heroux, Benoit Gauzere, Pascal Vasseur, Sebastien Adam, Paul Honeine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:599-608

Instance Specific Approximations for Submodular Maximization

Eric Balkanski, Sharon Qian, Yaron Singer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:609-618

Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment

Philip J Ball, Cong Lu, Jack Parker-Holder, Stephen Roberts; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:619-629

Regularized Online Allocation Problems: Fairness and Beyond

Santiago Balseiro, Haihao Lu, Vahab Mirrokni; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:630-639

Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers

Yujia Bao, Shiyu Chang, Regina Barzilay; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:640-650

Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models

Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:651-661

Compositional Video Synthesis with Action Graphs

Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach, Gal Chechik, Trevor Darrell, Amir Globerson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:662-673

Approximating a Distribution Using Weight Queries

Nadav Barak, Sivan Sabato; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:674-683

Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization

Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:684-693

Training Quantized Neural Networks to Global Optimality via Semidefinite Programming

Burak Bartan, Mert Pilanci; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:694-704

Beyond $log^2(T)$ regret for decentralized bandits in matching markets

Soumya Basu, Karthik Abinav Sankararaman, Abishek Sankararaman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:705-715

Optimal Thompson Sampling strategies for support-aware CVaR bandits

Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric Maillard; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:716-726

On Limited-Memory Subsampling Strategies for Bandits

Dorian Baudry, Yoan Russac, Olivier Cappé; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:727-737

Generalized Doubly Reparameterized Gradient Estimators

Matthias Bauer, Andriy Mnih; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:738-747

Directional Graph Networks

Dominique Beani, Saro Passaro, Vincent Létourneau, Will Hamilton, Gabriele Corso, Pietro Lió; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:748-758

Policy Analysis using Synthetic Controls in Continuous-Time

Alexis Bellot, Mihaela van der Schaar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:759-768

Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling

Gregory Benton, Wesley Maddox, Sanae Lotfi, Andrew Gordon Gordon Wilson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:769-779

TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer

Berkay Berabi, Jingxuan He, Veselin Raychev, Martin Vechev; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:780-791

Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis

Jeroen Berrevoets, Ahmed Alaa, Zhaozhi Qian, James Jordon, Alexander E. S. Gimson, Mihaela van der Schaar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:792-802

Learning from Biased Data: A Semi-Parametric Approach

Patrice Bertail, Stephan Clémençon, Yannick Guyonvarch, Nathan Noiry; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:803-812

Is Space-Time Attention All You Need for Video Understanding?

Gedas Bertasius, Heng Wang, Lorenzo Torresani; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:813-824

Confidence Scores Make Instance-dependent Label-noise Learning Possible

Antonin Berthon, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:825-836

Size-Invariant Graph Representations for Graph Classification Extrapolations

Beatrice Bevilacqua, Yangze Zhou, Bruno Ribeiro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:837-851

Principal Bit Analysis: Autoencoding with Schur-Concave Loss

Sourbh Bhadane, Aaron B Wagner, Jayadev Acharya; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:852-862

Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries

Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:863-873

Additive Error Guarantees for Weighted Low Rank Approximation

Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Maheshakya Wijewardena; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:874-883

Sample Complexity of Robust Linear Classification on Separated Data

Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:884-893

Finding k in Latent $k-$ polytope

Chiranjib Bhattacharyya, Ravindran Kannan, Amit Kumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:894-903

Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction

Hangrui Bi, Hengyi Wang, Chence Shi, Connor Coley, Jian Tang, Hongyu Guo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:904-913

TempoRL: Learning When to Act

André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:914-924

Follow-the-Regularized-Leader Routes to Chaos in Routing Games

Jakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski, Grzegorz Kosiorowski, Michał Misiurewicz, Georgios Piliouras; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:925-935

Neural Symbolic Regression that scales

Luca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurelien Lucchi, Giambattista Parascandolo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:936-945

Model Distillation for Revenue Optimization: Interpretable Personalized Pricing

Max Biggs, Wei Sun, Markus Ettl; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:946-956

Scalable Normalizing Flows for Permutation Invariant Densities

Marin Biloš, Stephan Günnemann; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:957-967

Online Learning for Load Balancing of Unknown Monotone Resource Allocation Games

Ilai Bistritz, Nicholas Bambos; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:968-979

Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision

Johan Björck, Xiangyu Chen, Christopher De Sa, Carla P Gomes, Kilian Weinberger; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:980-991

Multiplying Matrices Without Multiplying

Davis Blalock, John Guttag; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:992-1004

One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning

Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1005-1014

Black-box density function estimation using recursive partitioning

Erik Bodin, Zhenwen Dai, Neill Campbell, Carl Henrik Ek; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1015-1025

Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks

Cristian Bodnar, Fabrizio Frasca, Yuguang Wang, Nina Otter, Guido F Montufar, Pietro Lió, Michael Bronstein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1026-1037

The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning

Roberto Bondesan, Max Welling; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1038-1048

Offline Contextual Bandits with Overparameterized Models

David Brandfonbrener, William Whitney, Rajesh Ranganath, Joan Bruna; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1049-1058

High-Performance Large-Scale Image Recognition Without Normalization

Andy Brock, Soham De, Samuel L Smith, Karen Simonyan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1059-1071

Evaluating the Implicit Midpoint Integrator for Riemannian Hamiltonian Monte Carlo

James Brofos, Roy R Lederman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1072-1081

Reinforcement Learning of Implicit and Explicit Control Flow Instructions

Ethan Brooks, Janarthanan Rajendran, Richard L Lewis, Satinder Singh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1082-1091

Machine Unlearning for Random Forests

Jonathan Brophy, Daniel Lowd; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1092-1104

Value Alignment Verification

Daniel S Brown, Jordan Schneider, Anca Dragan, Scott Niekum; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1105-1115

Model-Free and Model-Based Policy Evaluation when Causality is Uncertain

David A Bruns-Smith; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1116-1126

Narrow Margins: Classification, Margins and Fat Tails

Francois Buet-Golfouse; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1127-1135

Differentially Private Correlation Clustering

Mark Bun, Marek Elias, Janardhan Kulkarni; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1136-1146

Disambiguation of Weak Supervision leading to Exponential Convergence rates

Vivien A Cabannnes, Francis Bach, Alessandro Rudi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1147-1157

Finite mixture models do not reliably learn the number of components

Diana Cai, Trevor Campbell, Tamara Broderick; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1158-1169

A Theory of Label Propagation for Subpopulation Shift

Tianle Cai, Ruiqi Gao, Jason Lee, Qi Lei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1170-1182

Lenient Regret and Good-Action Identification in Gaussian Process Bandits

Xu Cai, Selwyn Gomes, Jonathan Scarlett; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1183-1192

A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization

Hanqin Cai, Yuchen Lou, Daniel Mckenzie, Wotao Yin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1193-1203

GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training

Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1204-1215

On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization

Xu Cai, Jonathan Scarlett; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1216-1226

High-dimensional Experimental Design and Kernel Bandits

Romain Camilleri, Kevin Jamieson, Julian Katz-Samuels; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1227-1237

A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization

Andrew Campbell, Wenlong Chen, Vincent Stimper, Jose Miguel Hernandez-Lobato, Yichuan Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1238-1248

Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections

Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris Holmes, Mert Gurbuzbalaban, Umut Simsekli; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1249-1260

Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design

Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1261-1271

Learning from Similarity-Confidence Data

Yuzhou Cao, Lei Feng, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1272-1282

Parameter-free Locally Accelerated Conditional Gradients

Alejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1283-1293

Optimizing persistent homology based functions

Mathieu Carriere, Frederic Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1294-1303

Online Policy Gradient for Model Free Learning of Linear Quadratic Regulators with $\sqrt$T Regret

Asaf B Cassel, Tomer Koren; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1304-1313

Multi-Receiver Online Bayesian Persuasion

Matteo Castiglioni, Alberto Marchesi, Andrea Celli, Nicola Gatti; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1314-1323

Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data

Amnon Catav, Boyang Fu, Yazeed Zoabi, Ahuva Libi Weiss Meilik, Noam Shomron, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1324-1335

Disentangling syntax and semantics in the brain with deep networks

Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1336-1348

Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees

L. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1349-1361

Best Model Identification: A Rested Bandit Formulation

Leonardo Cella, Massimiliano Pontil, Claudio Gentile; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1362-1372

Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research

Johan Samir Obando Ceron, Pablo Samuel Castro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1373-1383

Learning Routines for Effective Off-Policy Reinforcement Learning

Edoardo Cetin, Oya Celiktutan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1384-1394

Learning Node Representations Using Stationary Flow Prediction on Large Payment and Cash Transaction Networks

Ciwan Ceylan, Salla Franzén, Florian T. Pokorny; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1395-1406

GRAND: Graph Neural Diffusion

Ben Chamberlain, James Rowbottom, Maria I Gorinova, Michael Bronstein, Stefan Webb, Emanuele Rossi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1407-1418

HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections

Ines Chami, Albert Gu, Dat P Nguyen, Christopher Re; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1419-1429

Goal-Conditioned Reinforcement Learning with Imagined Subgoals

Elliot Chane-Sane, Cordelia Schmid, Ivan Laptev; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1430-1440

Locally Private k-Means in One Round

Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1441-1451

Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment

Michael Chang, Sid Kaushik, Sergey Levine, Tom Griffiths; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1452-1462

Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection

Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Animashree Anandkumar, Sanja Fidler, Jose M Alvarez; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1463-1472

DeepWalking Backwards: From Embeddings Back to Graphs

Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos Tsourakakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1473-1483

Differentiable Spatial Planning using Transformers

Devendra Singh Chaplot, Deepak Pathak, Jitendra Malik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1484-1495

Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning

Henry J Charlesworth, Giovanni Montana; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1496-1506

Classification with Rejection Based on Cost-sensitive Classification

Nontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1507-1517

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills

Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan C Julian, Chelsea Finn, Sergey Levine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1518-1528

Unified Robust Semi-Supervised Variational Autoencoder

Xu Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1529-1538

Unsupervised Learning of Visual 3D Keypoints for Control

Boyuan Chen, Pieter Abbeel, Deepak Pathak; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1539-1549

Integer Programming for Causal Structure Learning in the Presence of Latent Variables

Rui Chen, Sanjeeb Dash, Tian Gao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1550-1560

Improved Corruption Robust Algorithms for Episodic Reinforcement Learning

Yifang Chen, Simon Du, Kevin Jamieson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1561-1570

Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks

Yongxin Chen, Jiaojiao Fan, Amirhossein Taghvaei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1571-1581

Neural Feature Matching in Implicit 3D Representations

Yunlu Chen, Basura Fernando, Hakan Bilen, Thomas Mensink, Efstratios Gavves; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1582-1593

Decentralized Riemannian Gradient Descent on the Stiefel Manifold

Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1594-1605

Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation

Chao Chen, Haoyu Geng, Nianzu Yang, Junchi Yan, Daiyue Xue, Jianping Yu, Xiaokang Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1606-1616

Mandoline: Model Evaluation under Distribution Shift

Mayee Chen, Karan Goel, Nimit S Sohoni, Fait Poms, Kayvon Fatahalian, Christopher Re; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1617-1629

Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation

Xiaohui Chen, Xu Han, Jiajing Hu, Francisco Ruiz, Liping Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1630-1639

CARTL: Cooperative Adversarially-Robust Transfer Learning

Dian Chen, Hongxin Hu, Qian Wang, Li Yinli, Cong Wang, Chao Shen, Qi Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1640-1650

Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case

Liyu Chen, Haipeng Luo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1651-1660

SpreadsheetCoder: Formula Prediction from Semi-structured Context

Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1661-1672

Large-Margin Contrastive Learning with Distance Polarization Regularizer

Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1673-1683

Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting

Yuzhou Chen, Ignacio Segovia, Yulia R. Gel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1684-1694

A Unified Lottery Ticket Hypothesis for Graph Neural Networks

Tianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, Zhangyang Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1695-1706

Network Inference and Influence Maximization from Samples

Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1707-1716

Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps

Renyi Chen, Molei Tao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1717-1727

Analysis of stochastic Lanczos quadrature for spectrum approximation

Tyler Chen, Thomas Trogdon, Shashanka Ubaru; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1728-1739

Large-Scale Multi-Agent Deep FBSDEs

Tianrong Chen, Ziyi O Wang, Ioannis Exarchos, Evangelos Theodorou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1740-1748

Representation Subspace Distance for Domain Adaptation Regression

Xinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1749-1759

Overcoming Catastrophic Forgetting by Bayesian Generative Regularization

Pei-Hung Chen, Wei Wei, Cho-Jui Hsieh, Bo Dai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1760-1770

Cyclically Equivariant Neural Decoders for Cyclic Codes

Xiangyu Chen, Min Ye; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1771-1780

A Receptor Skeleton for Capsule Neural Networks

Jintai Chen, Hongyun Yu, Chengde Qian, Danny Z Chen, Jian Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1781-1790

Accelerating Gossip SGD with Periodic Global Averaging

Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1791-1802

ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training

Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael Mahoney, Joseph Gonzalez; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1803-1813

SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation

Wuxinlin Cheng, Chenhui Deng, Zhiqiang Zhao, Yaohui Cai, Zhiru Zhang, Zhuo Feng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1814-1824

Self-supervised and Supervised Joint Training for Resource-rich Machine Translation

Yong Cheng, Wei Wang, Lu Jiang, Wolfgang Macherey; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1825-1835

Exact Optimization of Conformal Predictors via Incremental and Decremental Learning

Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1836-1845

Problem Dependent View on Structured Thresholding Bandit Problems

James Cheshire, Pierre Menard, Alexandra Carpentier; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1846-1854

Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré Recurrence

Yun Kuen Cheung, Georgios Piliouras; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1855-1865

Understanding and Mitigating Accuracy Disparity in Regression

Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon, Han Zhao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1866-1876

Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates

Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1877-1887

Light RUMs

Flavio Chierichetti, Ravi Kumar, Andrew Tomkins; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1888-1897

Parallelizing Legendre Memory Unit Training

Narsimha Reddy Chilkuri, Chris Eliasmith; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1898-1907

Quantifying and Reducing Bias in Maximum Likelihood Estimation of Structured Anomalies

Uthsav Chitra, Kimberly Ding, Jasper C.H. Lee, Benjamin J Raphael; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1908-1919

Robust Learning-Augmented Caching: An Experimental Study

Jakub Chłędowski, Adam Polak, Bartosz Szabucki, Konrad Tomasz Żołna; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1920-1930

Unifying Vision-and-Language Tasks via Text Generation

Jaemin Cho, Jie Lei, Hao Tan, Mohit Bansal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1931-1942

Learning from Nested Data with Ornstein Auto-Encoders

Youngwon Choi, Sungdong Lee, Joong-Ho Won; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1943-1952

Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning

Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1953-1963

Label-Only Membership Inference Attacks

Christopher A. Choquette-Choo, Florian Tramer, Nicholas Carlini, Nicolas Papernot; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1964-1974

Modeling Hierarchical Structures with Continuous Recursive Neural Networks

Jishnu Ray Chowdhury, Cornelia Caragea; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1975-1988

Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing

Filippos Christianos, Georgios Papoudakis, Muhammad A Rahman, Stefano V Albrecht; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1989-1998

Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization

Wesley Chung, Valentin Thomas, Marlos C. Machado, Nicolas Le Roux; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1999-2009

First-Order Methods for Wasserstein Distributionally Robust MDP

Julien Grand Clement, Christian Kroer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2010-2019

Phasic Policy Gradient

Karl W Cobbe, Jacob Hilton, Oleg Klimov, John Schulman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2020-2027

Riemannian Convex Potential Maps

Samuel Cohen, Brandon Amos, Yaron Lipman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2028-2038

Scaling Properties of Deep Residual Networks

Alain-Sam Cohen, Rama Cont, Alain Rossier, Renyuan Xu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2039-2048

Differentially-Private Clustering of Easy Instances

Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2049-2059

Improving Ultrametrics Embeddings Through Coresets

Vincent Cohen-Addad, Rémi De Joannis De Verclos, Guillaume Lagarde; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2060-2068

Correlation Clustering in Constant Many Parallel Rounds

Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrović, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2069-2078

Concentric mixtures of Mallows models for top-$k$ rankings: sampling and identifiability

Fabien Collas, Ekhine Irurozki; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2079-2088

Exploiting Shared Representations for Personalized Federated Learning

Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2089-2099

Differentiable Particle Filtering via Entropy-Regularized Optimal Transport

Adrien Corenflos, James Thornton, George Deligiannidis, Arnaud Doucet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2100-2111

Fairness and Bias in Online Selection

Jose Correa, Andres Cristi, Paul Duetting, Ashkan Norouzi-Fard; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2112-2121

Relative Deviation Margin Bounds

Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2122-2131

A Discriminative Technique for Multiple-Source Adaptation

Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2132-2143

Characterizing Fairness Over the Set of Good Models Under Selective Labels

Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2144-2155

Two-way kernel matrix puncturing: towards resource-efficient PCA and spectral clustering

Romain Couillet, Florent Chatelain, Nicolas Le Bihan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2156-2165

Explaining Time Series Predictions with Dynamic Masks

Jonathan Crabbé, Mihaela Van Der Schaar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2166-2177

Generalised Lipschitz Regularisation Equals Distributional Robustness

Zac Cranko, Zhan Shi, Xinhua Zhang, Richard Nock, Simon Kornblith; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2178-2188

Environment Inference for Invariant Learning

Elliot Creager, Joern-Henrik Jacobsen, Richard Zemel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2189-2200

Mind the Box: $l_1$-APGD for Sparse Adversarial Attacks on Image Classifiers

Francesco Croce, Matthias Hein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2201-2211

Parameterless Transductive Feature Re-representation for Few-Shot Learning

Wentao Cui, Yuhong Guo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2212-2221

Randomized Algorithms for Submodular Function Maximization with a $k$-System Constraint

Shuang Cui, Kai Han, Tianshuai Zhu, Jing Tang, Benwei Wu, He Huang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2222-2232

GBHT: Gradient Boosting Histogram Transform for Density Estimation

Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2233-2243

ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations

Chris Cummins, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Michael F P O’Boyle, Hugh Leather; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2244-2253

Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning

Sebastian Curi, Ilija Bogunovic, Andreas Krause; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2254-2264

Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability

Mihaela Curmei, Sarah Dean, Benjamin Recht; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2265-2275

Dynamic Balancing for Model Selection in Bandits and RL

Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2276-2285

ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases

Stéphane D’Ascoli, Hugo Touvron, Matthew L Leavitt, Ari S Morcos, Giulio Biroli, Levent Sagun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2286-2296

Consistent regression when oblivious outliers overwhelm

Tommaso D’Orsi, Gleb Novikov, David Steurer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2297-2306

Offline Reinforcement Learning with Pseudometric Learning

Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Léonard Hussenot, Olivier Pietquin, Matthieu Geist; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2307-2318

A Tale of Two Efficient and Informative Negative Sampling Distributions

Shabnam Daghaghi, Tharun Medini, Nicholas Meisburger, Beidi Chen, Mengnan Zhao, Anshumali Shrivastava; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2319-2329

SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels

Kunal Dahiya, Ananye Agarwal, Deepak Saini, Gururaj K, Jian Jiao, Amit Singh, Sumeet Agarwal, Purushottam Kar, Manik Varma; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2330-2340

Fixed-Parameter and Approximation Algorithms for PCA with Outliers

Yogesh Dahiya, Fedor Fomin, Fahad Panolan, Kirill Simonov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2341-2351

Sliced Iterative Normalizing Flows

Biwei Dai, Uros Seljak; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2352-2364

Convex Regularization in Monte-Carlo Tree Search

Tuan Q Dam, Carlo D’Eramo, Jan Peters, Joni Pajarinen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2365-2375

Demonstration-Conditioned Reinforcement Learning for Few-Shot Imitation

Christopher R. Dance, Julien Perez, Théo Cachet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2376-2387

Re-understanding Finite-State Representations of Recurrent Policy Networks

Mohamad H Danesh, Anurag Koul, Alan Fern, Saeed Khorram; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2388-2397

Newton Method over Networks is Fast up to the Statistical Precision

Amir Daneshmand, Gesualdo Scutari, Pavel Dvurechensky, Alexander Gasnikov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2398-2409

BasisDeVAE: Interpretable Simultaneous Dimensionality Reduction and Feature-Level Clustering with Derivative-Based Variational Autoencoders

Dominic Danks, Christopher Yau; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2410-2420

Intermediate Layer Optimization for Inverse Problems using Deep Generative Models

Giannis Daras, Joseph Dean, Ajil Jalal, Alex Dimakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2421-2432

Measuring Robustness in Deep Learning Based Compressive Sensing

Mohammad Zalbagi Darestani, Akshay S Chaudhari, Reinhard Heckel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2433-2444

SAINT-ACC: Safety-Aware Intelligent Adaptive Cruise Control for Autonomous Vehicles Using Deep Reinforcement Learning

Lokesh Chandra Das, Myounggyu Won; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2445-2455

Lipschitz normalization for self-attention layers with application to graph neural networks

George Dasoulas, Kevin Scaman, Aladin Virmaux; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2456-2466

Householder Sketch for Accurate and Accelerated Least-Mean-Squares Solvers

Jyotikrishna Dass, Rabi Mahapatra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2467-2477

Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data

Deepesh Data, Suhas Diggavi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2478-2488

Catformer: Designing Stable Transformers via Sensitivity Analysis

Jared Q Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher Re, Chelsea Finn, Percy Liang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2489-2499

Diffusion Source Identification on Networks with Statistical Confidence

Quinlan E Dawkins, Tianxi Li, Haifeng Xu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2500-2509

Bayesian Deep Learning via Subnetwork Inference

Erik Daxberger, Eric Nalisnick, James U Allingham, Javier Antoran, Jose Miguel Hernandez-Lobato; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2510-2521

Adversarial Robustness Guarantees for Random Deep Neural Networks

Giacomo De Palma, Bobak Kiani, Seth Lloyd; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2522-2534

High-Dimensional Gaussian Process Inference with Derivatives

Filip De Roos, Alexandra Gessner, Philipp Hennig; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2535-2545

Transfer-Based Semantic Anomaly Detection

Lucas Deecke, Lukas Ruff, Robert A. Vandermeulen, Hakan Bilen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2546-2558

Grid-Functioned Neural Networks

Javier Dehesa, Andrew Vidler, Julian Padget, Christof Lutteroth; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2559-2567

Multidimensional Scaling: Approximation and Complexity

Erik Demaine, Adam Hesterberg, Frederic Koehler, Jayson Lynch, John Urschel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2568-2578

What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?

Weijian Deng, Stephen Gould, Liang Zheng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2579-2589

Toward Better Generalization Bounds with Locally Elastic Stability

Zhun Deng, Hangfeng He, Weijie Su; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2590-2600

Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing

Yuan Deng, Sebastien Lahaie, Vahab Mirrokni, Song Zuo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2601-2610

Heterogeneity for the Win: One-Shot Federated Clustering

Don Kurian Dennis, Tian Li, Virginia Smith; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2611-2620

Kernel Continual Learning

Mohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao, Cees Snoek; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2621-2631

Bayesian Optimization over Hybrid Spaces

Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2632-2643

Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation

Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2644-2653

Versatile Verification of Tree Ensembles

Laurens Devos, Wannes Meert, Jesse Davis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2654-2664

On the Inherent Regularization Effects of Noise Injection During Training

Oussama Dhifallah, Yue Lu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2665-2675

Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time

Laxman Dhulipala, David Eisenstat, Jakub Łącki, Vahab Mirrokni, Jessica Shi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2676-2686

Learning Online Algorithms with Distributional Advice

Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Ali Vakilian, Nikos Zarifis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2687-2696

A Wasserstein Minimax Framework for Mixed Linear Regression

Theo Diamandis, Yonina Eldar, Alireza Fallah, Farzan Farnia, Asuman Ozdaglar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2697-2706

Context-Aware Online Collective Inference for Templated Graphical Models

Charles Dickens, Connor Pryor, Eriq Augustine, Alexander Miller, Lise Getoor; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2707-2716

ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables

Aleksandar Dimitriev, Mingyuan Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2717-2727

XOR-CD: Linearly Convergent Constrained Structure Generation

Fan Ding, Jianzhu Ma, Jinbo Xu, Yexiang Xue; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2728-2738

Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach

Tianyu Ding, Zhihui Zhu, Rene Vidal, Daniel P Robinson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2739-2748

Coded-InvNet for Resilient Prediction Serving Systems

Tuan Dinh, Kangwook Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2749-2759

Estimation and Quantization of Expected Persistence Diagrams

Vincent Divol, Theo Lacombe; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2760-2770

On Energy-Based Models with Overparametrized Shallow Neural Networks

Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2771-2782

Kernel-Based Reinforcement Learning: A Finite-Time Analysis

Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta, Emilie Kaufmann, Michal Valko; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2783-2792

Attention is not all you need: pure attention loses rank doubly exponentially with depth

Yihe Dong, Jean-Baptiste Cordonnier, Andreas Loukas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2793-2803

How rotational invariance of common kernels prevents generalization in high dimensions

Konstantin Donhauser, Mingqi Wu, Fanny Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2804-2814

Fast Stochastic Bregman Gradient Methods: Sharp Analysis and Variance Reduction

Radu Alexandru Dragomir, Mathieu Even, Hadrien Hendrikx; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2815-2825

Bilinear Classes: A Structural Framework for Provable Generalization in RL

Simon Du, Sham Kakade, Jason Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2826-2836

Improved Contrastive Divergence Training of Energy-Based Models

Yilun Du, Shuang Li, Joshua Tenenbaum, Igor Mordatch; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2837-2848

Order-Agnostic Cross Entropy for Non-Autoregressive Machine Translation

Cunxiao Du, Zhaopeng Tu, Jing Jiang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2849-2859

Putting the “Learning" into Learning-Augmented Algorithms for Frequency Estimation

Elbert Du, Franklyn Wang, Michael Mitzenmacher; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2860-2869

Estimating $α$-Rank from A Few Entries with Low Rank Matrix Completion

Yali Du, Xue Yan, Xu Chen, Jun Wang, Haifeng Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2870-2879

Learning Diverse-Structured Networks for Adversarial Robustness

Xuefeng Du, Jingfeng Zhang, Bo Han, Tongliang Liu, Yu Rong, Gang Niu, Junzhou Huang, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2880-2891

Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning

Yaqi Duan, Chi Jin, Zhiyuan Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2892-2902

Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network

Zhibin Duan, Dongsheng Wang, Bo Chen, Chaojie Wang, Wenchao Chen, Yewen Li, Jie Ren, Mingyuan Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2903-2913

Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics

Arkopal Dutt, Andrey Lokhov, Marc D Vuffray, Sidhant Misra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2914-2925

Reinforcement Learning Under Moral Uncertainty

Adrien Ecoffet, Joel Lehman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2926-2936

Confidence-Budget Matching for Sequential Budgeted Learning

Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2937-2947

Self-Paced Context Evaluation for Contextual Reinforcement Learning

Theresa Eimer, André Biedenkapp, Frank Hutter, Marius Lindauer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2948-2958

Provably Strict Generalisation Benefit for Equivariant Models

Bryn Elesedy, Sheheryar Zaidi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2959-2969

Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-Object Representations

Patrick Emami, Pan He, Sanjay Ranka, Anand Rangarajan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2970-2981

Implicit Bias of Linear RNNs

Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson K Fletcher; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2982-2992

Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs

Tolga Ergen, Mert Pilanci; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2993-3003

Revealing the Structure of Deep Neural Networks via Convex Duality

Tolga Ergen, Mert Pilanci; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3004-3014

Whitening for Self-Supervised Representation Learning

Aleksandr Ermolov, Aliaksandr Siarohin, Enver Sangineto, Nicu Sebe; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3015-3024

Graph Mixture Density Networks

Federico Errica, Davide Bacciu, Alessio Micheli; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3025-3035

Cross-Gradient Aggregation for Decentralized Learning from Non-IID Data

Yasaman Esfandiari, Sin Yong Tan, Zhanhong Jiang, Aditya Balu, Ethan Herron, Chinmay Hegde, Soumik Sarkar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3036-3046

Weight-covariance alignment for adversarially robust neural networks

Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy Hospedales; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3047-3056

Data augmentation for deep learning based accelerated MRI reconstruction with limited data

Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3057-3067

Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks

Xuhui Fan, Bin Li, Yaqiong Li, Scott A. Sisson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3068-3077

Model-based Reinforcement Learning for Continuous Control with Posterior Sampling

Ying Fan, Yifei Ming; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3078-3087

SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies

Linxi Fan, Guanzhi Wang, De-An Huang, Zhiding Yu, Li Fei-Fei, Yuke Zhu, Animashree Anandkumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3088-3099

On Estimation in Latent Variable Models

Guanhua Fang, Ping Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3100-3110

On Variational Inference in Biclustering Models

Guanhua Fang, Ping Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3111-3121

Learning Bounds for Open-Set Learning

Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3122-3132

Streaming Bayesian Deep Tensor Factorization

Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3133-3142

PID Accelerated Value Iteration Algorithm

Amir-Massoud Farahmand, Mohammad Ghavamzadeh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3143-3153

Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise

Vivek Farias, Andrew A Li, Tianyi Peng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3154-3163

Connecting Optimal Ex-Ante Collusion in Teams to Extensive-Form Correlation: Faster Algorithms and Positive Complexity Results

Gabriele Farina, Andrea Celli, Nicola Gatti, Tuomas Sandholm; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3164-3173

Train simultaneously, generalize better: Stability of gradient-based minimax learners

Farzan Farnia, Asuman Ozdaglar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3174-3185

Unbalanced minibatch Optimal Transport; applications to Domain Adaptation

Kilian Fatras, Thibault Sejourne, Rémi Flamary, Nicolas Courty; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3186-3197

Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach

Yingjie Fei, Zhuoran Yang, Zhaoran Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3198-3207

Lossless Compression of Efficient Private Local Randomizers

Vitaly Feldman, Kunal Talwar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3208-3219

Dimensionality Reduction for the Sum-of-Distances Metric

Zhili Feng, Praneeth Kacham, David Woodruff; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3220-3229

Reserve Price Optimization for First Price Auctions in Display Advertising

Zhe Feng, Sebastien Lahaie, Jon Schneider, Jinchao Ye; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3230-3239

Uncertainty Principles of Encoding GANs

Ruili Feng, Zhouchen Lin, Jiapeng Zhu, Deli Zhao, Jingren Zhou, Zheng-Jun Zha; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3240-3251

Pointwise Binary Classification with Pairwise Confidence Comparisons

Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3252-3262

Provably Correct Optimization and Exploration with Non-linear Policies

Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3263-3273

KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation

Haozhe Feng, Zhaoyang You, Minghao Chen, Tianye Zhang, Minfeng Zhu, Fei Wu, Chao Wu, Wei Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3274-3283

Understanding Noise Injection in GANs

Ruili Feng, Deli Zhao, Zheng-Jun Zha; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3284-3293

GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings

Matthias Fey, Jan E. Lenssen, Frank Weichert, Jure Leskovec; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3294-3304

PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning

Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3305-3317

A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups

Marc Finzi, Max Welling, Andrew Gordon Wilson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3318-3328

Few-Shot Conformal Prediction with Auxiliary Tasks

Adam Fisch, Tal Schuster, Tommi Jaakkola, Dr.Regina Barzilay; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3329-3339

Scalable Certified Segmentation via Randomized Smoothing

Marc Fischer, Maximilian Baader, Martin Vechev; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3340-3351

What’s in the Box? Exploring the Inner Life of Neural Networks with Robust Rules

Jonas Fischer, Anna Olah, Jilles Vreeken; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3352-3362

Online Learning with Optimism and Delay

Genevieve E Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3363-3373

Online A-Optimal Design and Active Linear Regression

Xavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3374-3383

Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design

Adam Foster, Desi R Ivanova, Ilyas Malik, Tom Rainforth; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3384-3395

Efficient Online Learning for Dynamic k-Clustering

Dimitris Fotakis, Georgios Piliouras, Stratis Skoulakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3396-3406

Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning

Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3407-3416

Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins

Spencer Frei, Yuan Cao, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3417-3426

Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise

Spencer Frei, Yuan Cao, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3427-3438

Post-selection inference with HSIC-Lasso

Tobias Freidling, Benjamin Poignard, Héctor Climente-González, Makoto Yamada; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3439-3448

Variational Data Assimilation with a Learned Inverse Observation Operator

Thomas Frerix, Dmitrii Kochkov, Jamie Smith, Daniel Cremers, Michael Brenner, Stephan Hoyer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3449-3458

Bayesian Quadrature on Riemannian Data Manifolds

Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3459-3468

Learn-to-Share: A Hardware-friendly Transfer Learning Framework Exploiting Computation and Parameter Sharing

Cheng Fu, Hanxian Huang, Xinyun Chen, Yuandong Tian, Jishen Zhao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3469-3479

Learning Task Informed Abstractions

Xiang Fu, Ge Yang, Pulkit Agrawal, Tommi Jaakkola; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3480-3491

Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference

Yonggan Fu, Qixuan Yu, Meng Li, Vikas Chandra, Yingyan Lin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3492-3504

Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators

Yonggan Fu, Yongan Zhang, Yang Zhang, David Cox, Yingyan Lin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3505-3517

A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation

Scott Fujimoto, David Meger, Doina Precup; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3518-3529

Learning disentangled representations via product manifold projection

Marco Fumero, Luca Cosmo, Simone Melzi, Emanuele Rodola; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3530-3540

Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning

Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3541-3552

An Information-Geometric Distance on the Space of Tasks

Yansong Gao, Pratik Chaudhari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3553-3563

Maximum Mean Discrepancy Test is Aware of Adversarial Attacks

Ruize Gao, Feng Liu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3564-3575

Unsupervised Co-part Segmentation through Assembly

Qingzhe Gao, Bin Wang, Libin Liu, Baoquan Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3576-3586

Discriminative Complementary-Label Learning with Weighted Loss

Yi Gao, Min-Ling Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3587-3597

RATT: Leveraging Unlabeled Data to Guarantee Generalization

Saurabh Garg, Sivaraman Balakrishnan, Zico Kolter, Zachary Lipton; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3598-3609

On Proximal Policy Optimization’s Heavy-tailed Gradients

Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3610-3619

What does LIME really see in images?

Damien Garreau, Dina Mardaoui; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3620-3629

Parametric Graph for Unimodal Ranking Bandit

Camille-Sovanneary Gauthier, Romaric Gaudel, Elisa Fromont, Boammani Aser Lompo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3630-3639

Let’s Agree to Degree: Comparing Graph Convolutional Networks in the Message-Passing Framework

Floris Geerts, Filip Mazowiecki, Guillermo Perez; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3640-3649

On the difficulty of unbiased alpha divergence minimization

Tomas Geffner, Justin Domke; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3650-3659

How and Why to Use Experimental Data to Evaluate Methods for Observational Causal Inference

Amanda M Gentzel, Purva Pruthi, David Jensen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3660-3671

Strategic Classification in the Dark

Ganesh Ghalme, Vineet Nair, Itay Eilat, Inbal Talgam-Cohen, Nir Rosenfeld; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3672-3681

EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL

Seyed Kamyar Seyed Ghasemipour, Dale Schuurmans, Shixiang Shane Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3682-3691

Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message

Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Amer Sinha; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3692-3701

The Power of Adaptivity for Stochastic Submodular Cover

Rohan Ghuge, Anupam Gupta, Viswanath Nagarajan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3702-3712

Differentially Private Quantiles

Jennifer Gillenwater, Matthew Joseph, Alex Kulesza; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3713-3722

Query Complexity of Adversarial Attacks

Grzegorz Gluch, Rüdiger Urbanke; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3723-3733

Spectral Normalisation for Deep Reinforcement Learning: An Optimisation Perspective

Florin Gogianu, Tudor Berariu, Mihaela C Rosca, Claudia Clopath, Lucian Busoniu, Razvan Pascanu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3734-3744

12-Lead ECG Reconstruction via Koopman Operators

Tomer Golany, Kira Radinsky, Daniel Freedman, Saar Minha; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3745-3754

Function Contrastive Learning of Transferable Meta-Representations

Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wuthrich, Bernhard Schölkopf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3755-3765

Active Slices for Sliced Stein Discrepancy

Wenbo Gong, Kaibo Zhang, Yingzhen Li, Jose Miguel Hernandez-Lobato; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3766-3776

On the Problem of Underranking in Group-Fair Ranking

Sruthi Gorantla, Amit Deshpande, Anand Louis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3777-3787

MARINA: Faster Non-Convex Distributed Learning with Compression

Eduard Gorbunov, Konstantin P. Burlachenko, Zhize Li, Peter Richtarik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3788-3798

Systematic Analysis of Cluster Similarity Indices: How to Validate Validation Measures

Martijn M Gösgens, Alexey Tikhonov, Liudmila Prokhorenkova; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3799-3808

Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline

Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3809-3820

Dissecting Supervised Constrastive Learning

Florian Graf, Christoph Hofer, Marc Niethammer, Roland Kwitt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3821-3830

Oops I Took A Gradient: Scalable Sampling for Discrete Distributions

Will Grathwohl, Kevin Swersky, Milad Hashemi, David Duvenaud, Chris Maddison; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3831-3841

Detecting Rewards Deterioration in Episodic Reinforcement Learning

Ido Greenberg, Shie Mannor; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3842-3853

Crystallization Learning with the Delaunay Triangulation

Jiaqi Gu, Guosheng Yin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3854-3863

AutoAttend: Automated Attention Representation Search

Chaoyu Guan, Xin Wang, Wenwu Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3864-3874

Operationalizing Complex Causes: A Pragmatic View of Mediation

Limor Gultchin, David Watson, Matt Kusner, Ricardo Silva; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3875-3885

On a Combination of Alternating Minimization and Nesterov’s Momentum

Sergey Guminov, Pavel Dvurechensky, Nazarii Tupitsa, Alexander Gasnikov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3886-3898

Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic Games

Hongyi Guo, Zuyue Fu, Zhuoran Yang, Zhaoran Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3899-3909

Adversarial Policy Learning in Two-player Competitive Games

Wenbo Guo, Xian Wu, Sui Huang, Xinyu Xing; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3910-3919

Soft then Hard: Rethinking the Quantization in Neural Image Compression

Zongyu Guo, Zhizheng Zhang, Runsen Feng, Zhibo Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3920-3929

UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning

Tarun Gupta, Anuj Mahajan, Bei Peng, Wendelin Boehmer, Shimon Whiteson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3930-3941

Distribution-Free Calibration Guarantees for Histogram Binning without Sample Splitting

Chirag Gupta, Aaditya Ramdas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3942-3952

Correcting Exposure Bias for Link Recommendation

Shantanu Gupta, Hao Wang, Zachary Lipton, Yuyang Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3953-3963

The Heavy-Tail Phenomenon in SGD

Mert Gurbuzbalaban, Umut Simsekli, Lingjiong Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3964-3975

Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks

Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3976-3987

Adapting to Delays and Data in Adversarial Multi-Armed Bandits

Andras Gyorgy, Pooria Joulani; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3988-3997

Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning

Hassan Hafez-Kolahi, Behrad Moniri, Shohreh Kasaei, Mahdieh Soleymani Baghshah; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3998-4007

Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach

Nadav Hallak, Panayotis Mertikopoulos, Volkan Cevher; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4008-4017

Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient Exploration

Seungyul Han, Youngchul Sung; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4018-4029

Adversarial Combinatorial Bandits with General Non-linear Reward Functions

Yanjun Han, Yining Wang, Xi Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4030-4039

A Collective Learning Framework to Boost GNN Expressiveness for Node Classification

Mengyue Hang, Jennifer Neville, Bruno Ribeiro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4040-4050

Grounding Language to Entities and Dynamics for Generalization in Reinforcement Learning

Austin W. Hanjie, Victor Y Zhong, Karthik Narasimhan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4051-4062

Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient

Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvari, Mengdi Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4063-4073

Bootstrapping Fitted Q-Evaluation for Off-Policy Inference

Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvari, Mengdi Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4074-4084

Compressed Maximum Likelihood

Yi Hao, Alon Orlitsky; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4085-4095

Valid Causal Inference with (Some) Invalid Instruments

Jason S Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4096-4106

Model Performance Scaling with Multiple Data Sources

Tatsunori Hashimoto; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4107-4116

Hierarchical VAEs Know What They Don’t Know

Jakob D. Drachmann Havtorn, Jes Frellsen, Soren Hauberg, Lars Maaløe; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4117-4128

Defense against backdoor attacks via robust covariance estimation

Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4129-4139

Boosting for Online Convex Optimization

Elad Hazan, Karan Singh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4140-4149

PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models

Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4150-4159

SoundDet: Polyphonic Moving Sound Event Detection and Localization from Raw Waveform

Yuhang He, Niki Trigoni, Andrew Markham; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4160-4170

Logarithmic Regret for Reinforcement Learning with Linear Function Approximation

Jiafan He, Dongruo Zhou, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4171-4180

Finding Relevant Information via a Discrete Fourier Expansion

Mohsen Heidari, Jithin Sreedharan, Gil I Shamir, Wojciech Szpankowski; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4181-4191

Zeroth-Order Non-Convex Learning via Hierarchical Dual Averaging

Amélie Héliou, Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4192-4202

Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity

Ryan Henderson, Djork-Arné Clevert, Floriane Montanari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4203-4213

Muesli: Combining Improvements in Policy Optimization

Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado Van Hasselt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4214-4226

Learning Representations by Humans, for Humans

Sophie Hilgard, Nir Rosenfeld, Mahzarin R Banaji, Jack Cao, David Parkes; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4227-4238

Optimizing Black-box Metrics with Iterative Example Weighting

Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Mahdi Milani Fard, Sanmi Koyejo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4239-4249

Trees with Attention for Set Prediction Tasks

Roy Hirsch, Ran Gilad-Bachrach; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4250-4261

Multiplicative Noise and Heavy Tails in Stochastic Optimization

Liam Hodgkinson, Michael Mahoney; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4262-4274

MC-LSTM: Mass-Conserving LSTM

Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey S Nearing, Sepp Hochreiter, Guenter Klambauer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4275-4286

Learning Curves for Analysis of Deep Networks

Derek Hoiem, Tanmay Gupta, Zhizhong Li, Michal Shlapentokh-Rothman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4287-4296

Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes

Peter Holderrieth, Michael J Hutchinson, Yee Whye Teh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4297-4307

Latent Programmer: Discrete Latent Codes for Program Synthesis

Joey Hong, David Dohan, Rishabh Singh, Charles Sutton, Manzil Zaheer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4308-4318

Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication

Sangwoo Hong, Heecheol Yang, Youngseok Yoon, Taehyun Cho, Jungwoo Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4319-4327

Federated Learning of User Verification Models Without Sharing Embeddings

Hossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph Soriaga, Max Welling; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4328-4336

The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets

Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4337-4348

Near-Optimal Representation Learning for Linear Bandits and Linear RL

Jiachen Hu, Xiaoyu Chen, Chi Jin, Lihong Li, Liwei Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4349-4358

On the Random Conjugate Kernel and Neural Tangent Kernel

Zhengmian Hu, Heng Huang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4359-4368

Off-Belief Learning

Hengyuan Hu, Adam Lerer, Brandon Cui, Luis Pineda, Noam Brown, Jakob Foerster; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4369-4379

Generalizable Episodic Memory for Deep Reinforcement Learning

Hao Hu, Jianing Ye, Guangxiang Zhu, Zhizhou Ren, Chongjie Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4380-4390

A Scalable Deterministic Global Optimization Algorithm for Clustering Problems

Kaixun Hua, Mingfei Shi, Yankai Cao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4391-4401

On Recovering from Modeling Errors Using Testing Bayesian Networks

Haiying Huang, Adnan Darwiche; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4402-4411

A Novel Sequential Coreset Method for Gradient Descent Algorithms

Jiawei Huang, Ruomin Huang, Wenjie Liu, Nikolaos Freris, Hu Ding; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4412-4422

FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis

Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4423-4434

STRODE: Stochastic Boundary Ordinary Differential Equation

Hengguan Huang, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4435-4445

A Riemannian Block Coordinate Descent Method for Computing the Projection Robust Wasserstein Distance

Minhui Huang, Shiqian Ma, Lifeng Lai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4446-4455

Projection Robust Wasserstein Barycenters

Minhui Huang, Shiqian Ma, Lifeng Lai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4456-4465

Accurate Post Training Quantization With Small Calibration Sets

Itay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, Daniel Soudry; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4466-4475

Learning and Planning in Complex Action Spaces

Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Mohammadamin Barekatain, Simon Schmitt, David Silver; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4476-4486

Generative Adversarial Transformers

Drew A Hudson, Larry Zitnick; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4487-4499

Neural Pharmacodynamic State Space Modeling

Zeshan M Hussain, Rahul G. Krishnan, David Sontag; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4500-4510

Hyperparameter Selection for Imitation Learning

Léonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphael Marinier, Lukasz Stafiniak, Manu Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4511-4522

Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions

Todd Huster, Jeremy Cohen, Zinan Lin, Kevin Chan, Charles Kamhoua, Nandi O. Leslie, Cho-Yu Jason Chiang, Vyas Sekar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4523-4532

LieTransformer: Equivariant Self-Attention for Lie Groups

Michael J Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, Hyunjik Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4533-4543

Crowdsourcing via Annotator Co-occurrence Imputation and Provable Symmetric Nonnegative Matrix Factorization

Shahana Ibrahim, Xiao Fu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4544-4554

Selecting Data Augmentation for Simulating Interventions

Maximilian Ilse, Jakub M Tomczak, Patrick Forré; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4555-4562

Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning

Alexander Immer, Matthias Bauer, Vincent Fortuin, Gunnar Rätsch, Khan Mohammad Emtiyaz; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4563-4573

Active Learning for Distributionally Robust Level-Set Estimation

Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4574-4584

Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization

Hedda Cohen Indelman, Tamir Hazan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4585-4595

Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning

Shariq Iqbal, Christian A Schroeder De Witt, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4596-4606

Randomized Exploration in Reinforcement Learning with General Value Function Approximation

Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4607-4616

Distributed Second Order Methods with Fast Rates and Compressed Communication

Rustem Islamov, Xun Qian, Peter Richtarik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4617-4628

What Are Bayesian Neural Network Posteriors Really Like?

Pavel Izmailov, Sharad Vikram, Matthew D Hoffman, Andrew Gordon Gordon Wilson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4629-4640

How to Learn when Data Reacts to Your Model: Performative Gradient Descent

Zachary Izzo, Lexing Ying, James Zou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4641-4650

Perceiver: General Perception with Iterative Attention

Andrew Jaegle, Felix Gimeno, Andy Brock, Oriol Vinyals, Andrew Zisserman, Joao Carreira; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4651-4664

Imitation by Predicting Observations

Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4665-4676

Local Correlation Clustering with Asymmetric Classification Errors

Jafar Jafarov, Sanchit Kalhan, Konstantin Makarychev, Yury Makarychev; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4677-4686

Alternative Microfoundations for Strategic Classification

Meena Jagadeesan, Celestine Mendler-Dünner, Moritz Hardt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4687-4697

Robust Density Estimation from Batches: The Best Things in Life are (Nearly) Free

Ayush Jain, Alon Orlitsky; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4698-4708

Instance-Optimal Compressed Sensing via Posterior Sampling

Ajil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4709-4720

Fairness for Image Generation with Uncertain Sensitive Attributes

Ajil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alex Dimakis, Eric Price; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4721-4732

Feature Clustering for Support Identification in Extreme Regions

Hamid Jalalzai, Rémi Leluc; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4733-4743

Improved Regret Bounds of Bilinear Bandits using Action Space Analysis

Kyoungseok Jang, Kwang-Sung Jun, Se-Young Yun, Wanmo Kang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4744-4754

Inverse Decision Modeling: Learning Interpretable Representations of Behavior

Daniel Jarrett, Alihan Hüyük, Mihaela Van Der Schaar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4755-4771

Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization

Stanislaw Jastrzebski, Devansh Arpit, Oliver Astrand, Giancarlo B Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J Geras; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4772-4784

Policy Gradient Bayesian Robust Optimization for Imitation Learning

Zaynah Javed, Daniel S Brown, Satvik Sharma, Jerry Zhu, Ashwin Balakrishna, Marek Petrik, Anca Dragan, Ken Goldberg; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4785-4796

In-Database Regression in Input Sparsity Time

Rajesh Jayaram, Alireza Samadian, David Woodruff, Peng Ye; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4797-4806

Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics

Vivek Jayaram, John Thickstun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4807-4818

Objective Bound Conditional Gaussian Process for Bayesian Optimization

Taewon Jeong, Heeyoung Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4819-4828

Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding

Andrew Jesson, Sören Mindermann, Yarin Gal, Uri Shalit; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4829-4838

DeepReDuce: ReLU Reduction for Fast Private Inference

Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4839-4849

Factor-analytic inverse regression for high-dimension, small-sample dimensionality reduction

Aditi Jha, Michael J. Morais, Jonathan W Pillow; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4850-4859

Fast margin maximization via dual acceleration

Ziwei Ji, Nathan Srebro, Matus Telgarsky; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4860-4869

Marginalized Stochastic Natural Gradients for Black-Box Variational Inference

Geng Ji, Debora Sujono, Erik B Sudderth; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4870-4881

Bilevel Optimization: Convergence Analysis and Enhanced Design

Kaiyi Ji, Junjie Yang, Yingbin Liang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4882-4892

Efficient Statistical Tests: A Neural Tangent Kernel Approach

Sheng Jia, Ehsan Nezhadarya, Yuhuai Wu, Jimmy Ba; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4893-4903

Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4904-4916

Multi-Dimensional Classification via Sparse Label Encoding

Bin-Bin Jia, Min-Ling Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4917-4926

Self-Damaging Contrastive Learning

Ziyu Jiang, Tianlong Chen, Bobak J Mortazavi, Zhangyang Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4927-4939

Prioritized Level Replay

Minqi Jiang, Edward Grefenstette, Tim Rocktäschel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4940-4950

Monotonic Robust Policy Optimization with Model Discrepancy

Yuankun Jiang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4951-4960

Approximation Theory of Convolutional Architectures for Time Series Modelling

Haotian Jiang, Zhong Li, Qianxiao Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4961-4970

Streaming and Distributed Algorithms for Robust Column Subset Selection

Shuli Jiang, Dennis Li, Irene Mengze Li, Arvind V Mahankali, David Woodruff; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4971-4981

Single Pass Entrywise-Transformed Low Rank Approximation

Yifei Jiang, Yi Li, Yiming Sun, Jiaxin Wang, David Woodruff; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4982-4991

The Emergence of Individuality

Jiechuan Jiang, Zongqing Lu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4992-5001

Online Selection Problems against Constrained Adversary

Zhihao Jiang, Pinyan Lu, Zhihao Gavin Tang, Yuhao Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5002-5012

Active Covering

Heinrich Jiang, Afshin Rostamizadeh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5013-5022

Emphatic Algorithms for Deep Reinforcement Learning

Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado Van Hasselt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5023-5033

Characterizing Structural Regularities of Labeled Data in Overparameterized Models

Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C Mozer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5034-5044

Optimal Streaming Algorithms for Multi-Armed Bandits

Tianyuan Jin, Keke Huang, Jing Tang, Xiaokui Xiao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5045-5054

Towards Tight Bounds on the Sample Complexity of Average-reward MDPs

Yujia Jin, Aaron Sidford; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5055-5064

Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits

Tianyuan Jin, Jing Tang, Pan Xu, Keke Huang, Xiaokui Xiao, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5065-5073

MOTS: Minimax Optimal Thompson Sampling

Tianyuan Jin, Pan Xu, Jieming Shi, Xiaokui Xiao, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5074-5083

Is Pessimism Provably Efficient for Offline RL?

Ying Jin, Zhuoran Yang, Zhaoran Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5084-5096

Adversarial Option-Aware Hierarchical Imitation Learning

Mingxuan Jing, Wenbing Huang, Fuchun Sun, Xiaojian Ma, Tao Kong, Chuang Gan, Lei Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5097-5106

Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information

Changhun Jo, Kangwook Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5107-5117

Provable Lipschitz Certification for Generative Models

Matt Jordan, Alex Dimakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5118-5126

Isometric Gaussian Process Latent Variable Model for Dissimilarity Data

Martin Jørgensen, Soren Hauberg; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5127-5136

On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models

Peizhong Ju, Xiaojun Lin, Ness Shroff; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5137-5147

Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits

Kwang-Sung Jun, Lalit Jain, Blake Mason, Houssam Nassif; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5148-5157

Detection of Signal in the Spiked Rectangular Models

Ji Hyung Jung, Hye Won Chung, Ji Oon Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5158-5167

Estimating Identifiable Causal Effects on Markov Equivalence Class through Double Machine Learning

Yonghan Jung, Jin Tian, Elias Bareinboim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5168-5179

A Nullspace Property for Subspace-Preserving Recovery

Mustafa D Kaba, Chong You, Daniel P Robinson, Enrique Mallada, Rene Vidal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5180-5188

Training Recurrent Neural Networks via Forward Propagation Through Time

Anil Kag, Venkatesh Saligrama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5189-5200

The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation

Peter Kairouz, Ziyu Liu, Thomas Steinke; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5201-5212

Practical and Private (Deep) Learning Without Sampling or Shuffling

Peter Kairouz, Brendan Mcmahan, Shuang Song, Om Thakkar, Abhradeep Thakurta, Zheng Xu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5213-5225

A Differentiable Point Process with Its Application to Spiking Neural Networks

Hiroshi Kajino; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5226-5235

Projection techniques to update the truncated SVD of evolving matrices with applications

Vasileios Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, Lior Horesh, Kenneth Clarkson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5236-5246

Optimal Off-Policy Evaluation from Multiple Logging Policies

Nathan Kallus, Yuta Saito, Masatoshi Uehara; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5247-5256

Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations

Angeliki Kamoutsi, Goran Banjac, John Lygeros; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5257-5268

Statistical Estimation from Dependent Data

Vardis Kandiros, Yuval Dagan, Nishanth Dikkala, Surbhi Goel, Constantinos Daskalakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5269-5278

SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes

Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Gordon Wilson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5279-5289

Variational Auto-Regressive Gaussian Processes for Continual Learning

Sanyam Kapoor, Theofanis Karaletsos, Thang D Bui; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5290-5300

Off-Policy Confidence Sequences

Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5301-5310

Learning from History for Byzantine Robust Optimization

Sai Praneeth Karimireddy, Lie He, Martin Jaggi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5311-5319

Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation

Masahiro Kato, Takeshi Teshima; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5320-5333

Improved Algorithms for Agnostic Pool-based Active Classification

Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5334-5344

When Does Data Augmentation Help With Membership Inference Attacks?

Yigitcan Kaya, Tudor Dumitras; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5345-5355

Regularized Submodular Maximization at Scale

Ehsan Kazemi, Shervin Minaee, Moran Feldman, Amin Karbasi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5356-5366

Prior Image-Constrained Reconstruction using Style-Based Generative Models

Varun A Kelkar, Mark Anastasio; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5367-5377

Self Normalizing Flows

Thomas A Keller, Jorn W.T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5378-5387

Interpretable Stability Bounds for Spectral Graph Filters

Henry Kenlay, Dorina Thanou, Xiaowen Dong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5388-5397

Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets

Thomas Kerdreux, Lewis Liu, Simon Lacoste-Julien, Damien Scieur; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5398-5408

Markpainting: Adversarial Machine Learning meets Inpainting

David Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross Anderson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5409-5419

Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm

Sajad Khodadadian, Zaiwei Chen, Siva Theja Maguluri; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5420-5431

Functional Space Analysis of Local GAN Convergence

Valentin Khrulkov, Artem Babenko, Ivan Oseledets; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5432-5442

"Hey, that’s not an ODE": Faster ODE Adjoints via Seminorms

Patrick Kidger, Ricky T. Q. Chen, Terry J Lyons; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5443-5452

Neural SDEs as Infinite-Dimensional GANs

Patrick Kidger, James Foster, Xuechen Li, Terry J Lyons; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5453-5463

GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training

Krishnateja Killamsetty, Durga S, Ganesh Ramakrishnan, Abir De, Rishabh Iyer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5464-5474

Improving Predictors via Combination Across Diverse Task Categories

Kwang In Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5475-5485

Self-Improved Retrosynthetic Planning

Junsu Kim, Sungsoo Ahn, Hankook Lee, Jinwoo Shin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5486-5495

Reward Identification in Inverse Reinforcement Learning

Kuno Kim, Shivam Garg, Kirankumar Shiragur, Stefano Ermon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5496-5505

I-BERT: Integer-only BERT Quantization

Sehoon Kim, Amir Gholami, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5506-5518

Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning

Taehyeong Kim, Injune Hwang, Hyundo Lee, Hyunseo Kim, Won-Seok Choi, Joseph J Lim, Byoung-Tak Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5519-5529

Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech

Jaehyeon Kim, Jungil Kong, Juhee Son; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5530-5540

A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning

Dong Ki Kim, Miao Liu, Matthew D Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan How; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5541-5550

Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations

Timothy D Kim, Thomas Z Luo, Jonathan W Pillow, Carlos Brody; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5551-5561

The Lipschitz Constant of Self-Attention

Hyunjik Kim, George Papamakarios, Andriy Mnih; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5562-5571

Unsupervised Skill Discovery with Bottleneck Option Learning

Jaekyeom Kim, Seohong Park, Gunhee Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5572-5582

ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision

Wonjae Kim, Bokyung Son, Ildoo Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5583-5594

Bias-Robust Bayesian Optimization via Dueling Bandits

Johannes Kirschner, Andreas Krause; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5595-5605

CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients

Dani Kiyasseh, Tingting Zhu, David A Clifton; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5606-5615

Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More

Johannes Klicpera, Marten Lienen, Stephan Günnemann; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5616-5627

Representational aspects of depth and conditioning in normalizing flows

Frederic Koehler, Viraj Mehta, Andrej Risteski; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5628-5636

WILDS: A Benchmark of in-the-Wild Distribution Shifts

Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran Haque, Sara M Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5637-5664

One-sided Frank-Wolfe algorithms for saddle problems

Vladimir Kolmogorov, Thomas Pock; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5665-5675

A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning

Abi Komanduru, Jean Honorio; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5676-5685

Consensus Control for Decentralized Deep Learning

Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian Stich; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5686-5696

A Distribution-dependent Analysis of Meta Learning

Mikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5697-5706

Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?

Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zügner, Sandhya Giri, Stephan Günnemann; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5707-5718

Kernel Stein Discrepancy Descent

Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5719-5730

Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch Size

Jack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, Rashmi Vinayak; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5731-5741

NeRF-VAE: A Geometry Aware 3D Scene Generative Model

Adam R Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokra, Danilo Jimenez Rezende; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5742-5752

Active Testing: Sample-Efficient Model Evaluation

Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5753-5763

High Confidence Generalization for Reinforcement Learning

James Kostas, Yash Chandak, Scott M Jordan, Georgios Theocharous, Philip Thomas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5764-5773

Offline Reinforcement Learning with Fisher Divergence Critic Regularization

Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5774-5783

ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks

Dmitry Kovalev, Egor Shulgin, Peter Richtarik, Alexander V Rogozin, Alexander Gasnikov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5784-5793

Revisiting Peng’s Q($λ$) for Modern Reinforcement Learning

Tadashi Kozuno, Yunhao Tang, Mark Rowland, Remi Munos, Steven Kapturowski, Will Dabney, Michal Valko, David Abel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5794-5804

Adapting to misspecification in contextual bandits with offline regression oracles

Sanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5805-5814

Out-of-Distribution Generalization via Risk Extrapolation (REx)

David Krueger, Ethan Caballero, Joern-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Remi Le Priol, Aaron Courville; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5815-5826

Near-Optimal Confidence Sequences for Bounded Random Variables

Arun K Kuchibhotla, Qinqing Zheng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5827-5837

Differentially Private Bayesian Inference for Generalized Linear Models

Tejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5838-5849

Bayesian Structural Adaptation for Continual Learning

Abhishek Kumar, Sunabha Chatterjee, Piyush Rai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5850-5860

Implicit rate-constrained optimization of non-decomposable objectives

Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5861-5871

A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples

Christian Kümmerle, Claudio M. Verdun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5872-5883

Meta-Thompson Sampling

Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5884-5893

Targeted Data Acquisition for Evolving Negotiation Agents

Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5894-5904

ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks

Jungmin Kwon, Jeongseop Kim, Hyunseo Park, In Kwon Choi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5905-5914

On the price of explainability for some clustering problems

Eduardo S Laber, Lucas Murtinho; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5915-5925

Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality

Jonathan Lacotte, Yifei Wang, Mert Pilanci; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5926-5936

Generalization Bounds in the Presence of Outliers: a Median-of-Means Study

Pierre Laforgue, Guillaume Staerman, Stephan Clémençon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5937-5947

Model Fusion for Personalized Learning

Thanh Chi Lam, Nghia Hoang, Bryan Kian Hsiang Low, Patrick Jaillet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5948-5958

Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix

Maximilian Lam, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, Michael Mitzenmacher; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5959-5968

Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions

Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5969-5978

Discovering symbolic policies with deep reinforcement learning

Mikel Landajuela, Brenden K Petersen, Sookyung Kim, Claudio P Santiago, Ruben Glatt, Nathan Mundhenk, Jacob F Pettit, Daniel Faissol; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5979-5989

Graph Cuts Always Find a Global Optimum for Potts Models (With a Catch)

Hunter Lang, David Sontag, Aravindan Vijayaraghavan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5990-5999

Efficient Message Passing for 0–1 ILPs with Binary Decision Diagrams

Jan-Hendrik Lange, Paul Swoboda; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6000-6010

CountSketches, Feature Hashing and the Median of Three

Kasper Green Larsen, Rasmus Pagh, Jakub Tětek; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6011-6020

MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space

Sophie C. Laturnus, Philipp Berens; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6021-6031

Improved Regret Bound and Experience Replay in Regularized Policy Iteration

Nevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6032-6042

LAMDA: Label Matching Deep Domain Adaptation

Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6043-6054

Gaussian Process-Based Real-Time Learning for Safety Critical Applications

Armin Lederer, Alejandro J Ordóñez Conejo, Korbinian A Maier, Wenxin Xiao, Jonas Umlauft, Sandra Hirche; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6055-6064

Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer

Seungwon Lee, Sima Behpour, Eric Eaton; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6065-6075

Fair Selective Classification Via Sufficiency

Joshua K Lee, Yuheng Bu, Deepta Rajan, Prasanna Sattigeri, Rameswar Panda, Subhro Das, Gregory W Wornell; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6076-6086

On-the-fly Rectification for Robust Large-Vocabulary Topic Inference

Moontae Lee, Sungjun Cho, Kun Dong, David Mimno, David Bindel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6087-6097

Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification

Dong Hoon Lee, Sae-Young Chung; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6098-6108

Continual Learning in the Teacher-Student Setup: Impact of Task Similarity

Sebastian Lee, Sebastian Goldt, Andrew Saxe; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6109-6119

OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation

Jongmin Lee, Wonseok Jeon, Byungjun Lee, Joelle Pineau, Kee-Eung Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6120-6130

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning

Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6131-6141

Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously

Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6142-6151

PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training

Kimin Lee, Laura M Smith, Pieter Abbeel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6152-6163

Near-Optimal Linear Regression under Distribution Shift

Qi Lei, Wei Hu, Jason Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6164-6174

Stability and Generalization of Stochastic Gradient Methods for Minimax Problems

Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6175-6186

Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot

Joel Z Leibo, Edgar A Dueñez-Guzman, Alexander Vezhnevets, John P Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6187-6199

Better Training using Weight-Constrained Stochastic Dynamics

Benedict Leimkuhler, Tiffany J Vlaar, Timothée Pouchon, Amos Storkey; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6200-6211

Globally-Robust Neural Networks

Klas Leino, Zifan Wang, Matt Fredrikson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6212-6222

Learning to Price Against a Moving Target

Renato Paes Leme, Balasubramanian Sivan, Yifeng Teng, Pratik Worah; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6223-6232

SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data

Maud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V. Bonilla, Theodoros Damoulas, Terry J Lyons; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6233-6242

Strategic Classification Made Practical

Sagi Levanon, Nir Rosenfeld; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6243-6253

Improved, Deterministic Smoothing for L_1 Certified Robustness

Alexander J Levine, Soheil Feizi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6254-6264

BASE Layers: Simplifying Training of Large, Sparse Models

Mike Lewis, Shruti Bhosale, Tim Dettmers, Naman Goyal, Luke Zettlemoyer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6265-6274

Run-Sort-ReRun: Escaping Batch Size Limitations in Sliced Wasserstein Generative Models

Jose Lezama, Wei Chen, Qiang Qiu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6275-6285

PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization

Zhize Li, Hongyan Bao, Xiangliang Zhang, Peter Richtarik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6286-6295

Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning

Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6296-6306

Winograd Algorithm for AdderNet

Wenshuo Li, Hanting Chen, Mingqiang Huang, Xinghao Chen, Chunjing Xu, Yunhe Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6307-6315

A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration

Yuhang Li, Shikuang Deng, Xin Dong, Ruihao Gong, Shi Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6316-6325

Privacy-Preserving Feature Selection with Secure Multiparty Computation

Xiling Li, Rafael Dowsley, Martine De Cock; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6326-6336

Theory of Spectral Method for Union of Subspaces-Based Random Geometry Graph

Gen Li, Yuantao Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6337-6345

MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning

Kevin Li, Abhishek Gupta, Ashwin Reddy, Vitchyr H Pong, Aurick Zhou, Justin Yu, Sergey Levine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6346-6356

Ditto: Fair and Robust Federated Learning Through Personalization

Tian Li, Shengyuan Hu, Ahmad Beirami, Virginia Smith; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6357-6368

Quantization Algorithms for Random Fourier Features

Xiaoyun Li, Ping Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6369-6380

Approximate Group Fairness for Clustering

Bo Li, Lijun Li, Ankang Sun, Chenhao Wang, Yingfan Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6381-6391

Sharper Generalization Bounds for Clustering

Shaojie Li, Yong Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6392-6402

Provably End-to-end Label-noise Learning without Anchor Points

Xuefeng Li, Tongliang Liu, Bo Han, Gang Niu, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6403-6413

A Novel Method to Solve Neural Knapsack Problems

Duanshun Li, Jing Liu, Dongeun Lee, Ali Seyedmazloom, Giridhar Kaushik, Kookjin Lee, Noseong Park; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6414-6424

Mixed Cross Entropy Loss for Neural Machine Translation

Haoran Li, Wei Lu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6425-6436

Training Graph Neural Networks with 1000 Layers

Guohao Li, Matthias Müller, Bernard Ghanem, Vladlen Koltun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6437-6449

Active Feature Acquisition with Generative Surrogate Models

Yang Li, Junier Oliva; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6450-6459

Partially Observed Exchangeable Modeling

Yang Li, Junier Oliva; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6460-6470

Testing DNN-based Autonomous Driving Systems under Critical Environmental Conditions

Zhong Li, Minxue Pan, Tian Zhang, Xuandong Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6471-6482

The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks

Xiaocheng Li, Chunlin Sun, Yinyu Ye; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6483-6492

Distributionally Robust Optimization with Markovian Data

Mengmeng Li, Tobias Sutter, Daniel Kuhn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6493-6503

Communication-Efficient Distributed SVD via Local Power Iterations

Xiang Li, Shusen Wang, Kun Chen, Zhihua Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6504-6514

FILTRA: Rethinking Steerable CNN by Filter Transform

Bo Li, Qili Wang, Gim Hee Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6515-6522

Online Unrelated Machine Load Balancing with Predictions Revisited

Shi Li, Jiayi Xian; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6523-6532

Asymptotic Normality and Confidence Intervals for Prediction Risk of the Min-Norm Least Squares Estimator

Zeng Li, Chuanlong Xie, Qinwen Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6533-6542

TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models

Zhuohan Li, Siyuan Zhuang, Shiyuan Guo, Danyang Zhuo, Hao Zhang, Dawn Song, Ion Stoica; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6543-6552

A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance

Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6553-6564

Towards Understanding and Mitigating Social Biases in Language Models

Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, Ruslan Salakhutdinov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6565-6576

Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability

Kaizhao Liang, Jacky Y Zhang, Boxin Wang, Zhuolin Yang, Sanmi Koyejo, Bo Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6577-6587

Parallel Droplet Control in MEDA Biochips using Multi-Agent Reinforcement Learning

Tung-Che Liang, Jin Zhou, Yun-Sheng Chan, Tsung-Yi Ho, Krishnendu Chakrabarty, Cy Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6588-6599

Information Obfuscation of Graph Neural Networks

Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6600-6610

Guided Exploration with Proximal Policy Optimization using a Single Demonstration

Gabriele Libardi, Gianni De Fabritiis, Sebastian Dittert; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6611-6620

Debiasing a First-order Heuristic for Approximate Bi-level Optimization

Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Q Davis, Adrian Weller; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6621-6630

Making transport more robust and interpretable by moving data through a small number of anchor points

Chi-Heng Lin, Mehdi Azabou, Eva Dyer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6631-6641

Straight to the Gradient: Learning to Use Novel Tokens for Neural Text Generation

Xiang Lin, Simeng Han, Shafiq Joty; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6642-6653

Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data

Tao Lin, Sai Praneeth Karimireddy, Sebastian Stich, Martin Jaggi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6654-6665

Generative Causal Explanations for Graph Neural Networks

Wanyu Lin, Hao Lan, Baochun Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6666-6679

Tractable structured natural-gradient descent using local parameterizations

Wu Lin, Frank Nielsen, Khan Mohammad Emtiyaz, Mark Schmidt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6680-6691

Active Learning of Continuous-time Bayesian Networks through Interventions

Dominik Linzner, Heinz Koeppl; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6692-6701

Phase Transitions, Distance Functions, and Implicit Neural Representations

Yaron Lipman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6702-6712

The Earth Mover’s Pinball Loss: Quantiles for Histogram-Valued Regression

Florian List; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6713-6724

Understanding Instance-Level Label Noise: Disparate Impacts and Treatments

Yang Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6725-6735

APS: Active Pretraining with Successor Features

Hao Liu, Pieter Abbeel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6736-6747

Learning by Turning: Neural Architecture Aware Optimisation

Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6748-6758

Dynamic Game Theoretic Neural Optimizer

Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6759-6769

Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks

Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6770-6780

Just Train Twice: Improving Group Robustness without Training Group Information

Evan Z Liu, Behzad Haghgoo, Annie S Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6781-6792

Event Outlier Detection in Continuous Time

Siqi Liu, Milos Hauskrecht; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6793-6803

Heterogeneous Risk Minimization

Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6804-6814

Stochastic Iterative Graph Matching

Linfeng Liu, Michael C Hughes, Soha Hassoun, Liping Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6815-6825

Cooperative Exploration for Multi-Agent Deep Reinforcement Learning

Iou-Jen Liu, Unnat Jain, Raymond A Yeh, Alexander Schwing; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6826-6836

Elastic Graph Neural Networks

Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6837-6849

One Pass Late Fusion Multi-view Clustering

Xinwang Liu, Li Liu, Qing Liao, Siwei Wang, Yi Zhang, Wenxuan Tu, Chang Tang, Jiyuan Liu, En Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6850-6859

Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition

Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6860-6870

From Local to Global Norm Emergence: Dissolving Self-reinforcing Substructures with Incremental Social Instruments

Yiwei Liu, Jiamou Liu, Kaibin Wan, Zhan Qin, Zijian Zhang, Bakhadyr Khoussainov, Liehuang Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6871-6881

A Value-Function-based Interior-point Method for Non-convex Bi-level Optimization

Risheng Liu, Xuan Liu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6882-6892

Selfish Sparse RNN Training

Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6893-6904

Temporal Difference Learning as Gradient Splitting

Rui Liu, Alex Olshevsky; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6905-6913

On Robust Mean Estimation under Coordinate-level Corruption

Zifan Liu, Jong Ho Park, Theodoros Rekatsinas, Christos Tzamos; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6914-6924

Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices

Evan Z Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6925-6935

How Do Adam and Training Strategies Help BNNs Optimization

Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6936-6946

SagaNet: A Small Sample Gated Network for Pediatric Cancer Diagnosis

Yuhan Liu, Shiliang Sun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6947-6956

Learning Deep Neural Networks under Agnostic Corrupted Supervision

Boyang Liu, Mengying Sun, Ding Wang, Pang-Ning Tan, Jiayu Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6957-6967

Leveraging Public Data for Practical Private Query Release

Terrance Liu, Giuseppe Vietri, Thomas Steinke, Jonathan Ullman, Steven Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6968-6977

Watermarking Deep Neural Networks with Greedy Residuals

Hanwen Liu, Zhenyu Weng, Yuesheng Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6978-6988

Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training

Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6989-7000

A Sharp Analysis of Model-based Reinforcement Learning with Self-Play

Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7001-7010

Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?

Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7011-7020

Group Fisher Pruning for Practical Network Compression

Liyang Liu, Shilong Zhang, Zhanghui Kuang, Aojun Zhou, Jing-Hao Xue, Xinjiang Wang, Yimin Chen, Wenming Yang, Qingmin Liao, Wayne Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7021-7032

Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport

Lewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7033-7044

Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent

Kangqiao Liu, Liu Ziyin, Masahito Ueda; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7045-7056

Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning

Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7057-7066

Relative Positional Encoding for Transformers with Linear Complexity

Antoine Liutkus, Ondřej Cı́fka, Shih-Lun Wu, Umut Simsekli, Yi-Hsuan Yang, Gael Richard; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7067-7079

Joint Online Learning and Decision-making via Dual Mirror Descent

Alfonso Lobos, Paul Grigas, Zheng Wen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7080-7089

Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian Approach

Federico Lopez, Beatrice Pozzetti, Steve Trettel, Michael Strube, Anna Wienhard; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7090-7101

HEMET: A Homomorphic-Encryption-Friendly Privacy-Preserving Mobile Neural Network Architecture

Qian Lou, Lei Jiang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7102-7110

Optimal Complexity in Decentralized Training

Yucheng Lu, Christopher De Sa; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7111-7123

DANCE: Enhancing saliency maps using decoys

Yang Young Lu, Wenbo Guo, Xinyu Xing, William Stafford Noble; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7124-7133

Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification

Nan Lu, Shida Lei, Gang Niu, Issei Sato, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7134-7144

Variance Reduced Training with Stratified Sampling for Forecasting Models

Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean Foster; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7145-7155

ACE: Explaining cluster from an adversarial perspective

Yang Young Lu, Timothy C Yu, Giancarlo Bonora, William Stafford Noble; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7156-7167

On Monotonic Linear Interpolation of Neural Network Parameters

James R Lucas, Juhan Bae, Michael R Zhang, Stanislav Fort, Richard Zemel, Roger B Grosse; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7168-7179

Improving Breadth-Wise Backpropagation in Graph Neural Networks Helps Learning Long-Range Dependencies.

Denis Lukovnikov, Asja Fischer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7180-7191

GraphDF: A Discrete Flow Model for Molecular Graph Generation

Youzhi Luo, Keqiang Yan, Shuiwang Ji; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7192-7203

Trajectory Diversity for Zero-Shot Coordination

Andrei Lupu, Brandon Cui, Hengyuan Hu, Jakob Foerster; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7204-7213

HyperHyperNetwork for the Design of Antenna Arrays

Shahar Lutati, Lior Wolf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7214-7223

Value Iteration in Continuous Actions, States and Time

Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7224-7234

Meta-Cal: Well-controlled Post-hoc Calibration by Ranking

Xingchen Ma, Matthew B. Blaschko; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7235-7245

Neural-Pull: Learning Signed Distance Function from Point clouds by Learning to Pull Space onto Surface

Baorui Ma, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7246-7257

Learning Stochastic Behaviour from Aggregate Data

Shaojun Ma, Shu Liu, Hongyuan Zha, Haomin Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7258-7267

Local Algorithms for Finding Densely Connected Clusters

Peter Macgregor, He Sun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7268-7278

Learning to Generate Noise for Multi-Attack Robustness

Divyam Madaan, Jinwoo Shin, Sung Ju Hwang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7279-7289

Learning Interaction Kernels for Agent Systems on Riemannian Manifolds

Mauro Maggioni, Jason J Miller, Hongda Qiu, Ming Zhong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7290-7300

Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning

Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7301-7312

Domain Generalization using Causal Matching

Divyat Mahajan, Shruti Tople, Amit Sharma; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7313-7324

Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness

Vien V. Mai, Mikael Johansson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7325-7335

Nonparametric Hamiltonian Monte Carlo

Carol Mak, Fabian Zaiser, Luke Ong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7336-7347

Exploiting structured data for learning contagious diseases under incomplete testing

Maggie Makar, Lauren West, David Hooper, Eric Horvitz, Erica Shenoy, John Guttag; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7348-7357

Near-Optimal Algorithms for Explainable k-Medians and k-Means

Konstantin Makarychev, Liren Shan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7358-7367

KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning

Ashok V Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7368-7378

Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels

Eran Malach, Pritish Kamath, Emmanuel Abbe, Nathan Srebro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7379-7389

Inverse Constrained Reinforcement Learning

Shehryar Malik, Usman Anwar, Alireza Aghasi, Ali Ahmed; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7390-7399

A Sampling-Based Method for Tensor Ring Decomposition

Osman Asif Malik, Stephen Becker; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7400-7411

Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity

Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7412-7422

Beyond the Pareto Efficient Frontier: Constraint Active Search for Multiobjective Experimental Design

Gustavo Malkomes, Bolong Cheng, Eric H Lee, Mike Mccourt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7423-7434

Consistent Nonparametric Methods for Network Assisted Covariate Estimation

Xueyu Mao, Deepayan Chakrabarti, Purnamrita Sarkar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7435-7446

Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs

Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7447-7458

Adaptive Sampling for Best Policy Identification in Markov Decision Processes

Aymen Al Marjani, Alexandre Proutiere; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7459-7468

Explanations for Monotonic Classifiers.

Joao Marques-Silva, Thomas Gerspacher, Martin C Cooper, Alexey Ignatiev, Nina Narodytska; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7469-7479

Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers

Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7480-7491

Blind Pareto Fairness and Subgroup Robustness

Natalia L Martinez, Martin A Bertran, Afroditi Papadaki, Miguel Rodrigues, Guillermo Sapiro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7492-7501

Necessary and sufficient conditions for causal feature selection in time series with latent common causes

Atalanti A Mastakouri, Bernhard Schölkopf, Dominik Janzing; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7502-7511

Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction

Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt Kusner, Arthur Gretton, Krikamol Muandet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7512-7523

Robust Unsupervised Learning via L-statistic Minimization

Andreas Maurer, Daniela Angela Parletta, Andrea Paudice, Massimiliano Pontil; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7524-7533

Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees

Alessio Mazzetto, Cyrus Cousins, Dylan Sam, Stephen H Bach, Eli Upfal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7534-7543

Fundamental Tradeoffs in Distributionally Adversarial Training

Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup Rao, Tung Mai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7544-7554

Leveraging Non-uniformity in First-order Non-convex Optimization

Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvari, Dale Schuurmans; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7555-7564

Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks

Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7565-7577

A theory of high dimensional regression with arbitrary correlations between input features and target functions: sample complexity, multiple descent curves and a hierarchy of phase transitions

Gabriel Mel, Surya Ganguli; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7578-7587

Neural Architecture Search without Training

Joe Mellor, Jack Turner, Amos Storkey, Elliot J Crowley; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7588-7598

Fast active learning for pure exploration in reinforcement learning

Pierre Menard, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7599-7608

UCB Momentum Q-learning: Correcting the bias without forgetting

Pierre Menard, Omar Darwiche Domingues, Xuedong Shang, Michal Valko; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7609-7618

An Integer Linear Programming Framework for Mining Constraints from Data

Tao Meng, Kai-Wei Chang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7619-7631

A statistical perspective on distillation

Aditya K Menon, Ankit Singh Rawat, Sashank Reddi, Seungyeon Kim, Sanjiv Kumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7632-7642

Learn2Hop: Learned Optimization on Rough Landscapes

Amil Merchant, Luke Metz, Samuel S Schoenholz, Ekin D Cubuk; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7643-7653

Counterfactual Credit Assignment in Model-Free Reinforcement Learning

Thomas Mesnard, Theophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas S Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Remi Munos; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7654-7664

Provably Efficient Learning of Transferable Rewards

Alberto Maria Metelli, Giorgia Ramponi, Alessandro Concetti, Marcello Restelli; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7665-7676

Mixed Nash Equilibria in the Adversarial Examples Game

Laurent Meunier, Meyer Scetbon, Rafael B Pinot, Jamal Atif, Yann Chevaleyre; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7677-7687

Learning in Nonzero-Sum Stochastic Games with Potentials

David H Mguni, Yutong Wu, Yali Du, Yaodong Yang, Ziyi Wang, Minne Li, Ying Wen, Joel Jennings, Jun Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7688-7699

EfficientTTS: An Efficient and High-Quality Text-to-Speech Architecture

Chenfeng Miao, Liang Shuang, Zhengchen Liu, Chen Minchuan, Jun Ma, Shaojun Wang, Jing Xiao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7700-7709

Outside the Echo Chamber: Optimizing the Performative Risk

John P Miller, Juan C Perdomo, Tijana Zrnic; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7710-7720

Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization

John P Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7721-7735

Signatured Deep Fictitious Play for Mean Field Games with Common Noise

Ming Min, Ruimeng Hu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7736-7747

Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation

Dongchan Min, Dong Bok Lee, Eunho Yang, Sung Ju Hwang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7748-7759

On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks

Hancheng Min, Salma Tarmoun, Rene Vidal, Enrique Mallada; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7760-7768

An Identifiable Double VAE For Disentangled Representations

Graziano Mita, Maurizio Filippone, Pietro Michiardi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7769-7779

Offline Meta-Reinforcement Learning with Advantage Weighting

Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7780-7791

The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization

Taiki Miyagawa, Akinori F Ebihara; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7792-7804

PODS: Policy Optimization via Differentiable Simulation

Miguel Angel Zamora Mora, Momchil Peychev, Sehoon Ha, Martin Vechev, Stelian Coros; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7805-7817

Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games

Dustin Morrill, Ryan D’Orazio, Marc Lanctot, James R Wright, Michael Bowling, Amy R Greenwald; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7818-7828

Neural Rough Differential Equations for Long Time Series

James Morrill, Cristopher Salvi, Patrick Kidger, James Foster; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7829-7838

Connecting Interpretability and Robustness in Decision Trees through Separation

Michal Moshkovitz, Yao-Yuan Yang, Kamalika Chaudhuri; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7839-7849

Outlier-Robust Optimal Transport

Debarghya Mukherjee, Aritra Guha, Justin M Solomon, Yuekai Sun, Mikhail Yurochkin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7850-7860

Oblivious Sketching for Logistic Regression

Alexander Munteanu, Simon Omlor, David Woodruff; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7861-7871

Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning

Tomoya Murata, Taiji Suzuki; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7872-7881

Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold

Kieran A Murphy, Carlos Esteves, Varun Jampani, Srikumar Ramalingam, Ameesh Makadia; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7882-7893

No-regret Algorithms for Capturing Events in Poisson Point Processes

Mojmir Mutny, Andreas Krause; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7894-7904

Online Limited Memory Neural-Linear Bandits with Likelihood Matching

Ofir Nabati, Tom Zahavy, Shie Mannor; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7905-7915

Quantitative Understanding of VAE as a Non-linearly Scaled Isometric Embedding

Akira Nakagawa, Keizo Kato, Taiji Suzuki; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7916-7926

GMAC: A Distributional Perspective on Actor-Critic Framework

Daniel W Nam, Younghoon Kim, Chan Y Park; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7927-7936

Memory-Efficient Pipeline-Parallel DNN Training

Deepak Narayanan, Amar Phanishayee, Kaiyu Shi, Xie Chen, Matei Zaharia; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7937-7947

Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering

Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7948-7957

Generating images with sparse representations

Charlie Nash, Jacob Menick, Sander Dieleman, Peter Battaglia; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7958-7968

Geometric convergence of elliptical slice sampling

Viacheslav Natarovskii, Daniel Rudolf, Björn Sprungk; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7969-7978

HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search

Niv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7979-7990

Emergent Social Learning via Multi-agent Reinforcement Learning

Kamal K Ndousse, Douglas Eck, Sergey Levine, Natasha Jaques; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7991-8004

Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information

Willie Neiswanger, Ke Alexander Wang, Stefano Ermon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8005-8015

Continuous Coordination As a Realistic Scenario for Lifelong Learning

Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville, Sarath Chandar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8016-8024

Policy Caches with Successor Features

Mark Nemecek, Ronald Parr; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8025-8033

Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners

Elias Chaibub Neto; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8034-8044

Incentivizing Compliance with Algorithmic Instruments

Dung Daniel T Ngo, Logan Stapleton, Vasilis Syrgkanis, Steven Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8045-8055

On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths

Quynh Nguyen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8056-8062

Value-at-Risk Optimization with Gaussian Processes

Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8063-8072

Cross-model Back-translated Distillation for Unsupervised Machine Translation

Xuan-Phi Nguyen, Shafiq Joty, Thanh-Tung Nguyen, Kui Wu, Ai Ti Aw; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8073-8083

Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search

Vu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8084-8095

Interactive Learning from Activity Description

Khanh X Nguyen, Dipendra Misra, Robert Schapire, Miroslav Dudik, Patrick Shafto; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8096-8108

Nonmyopic Multifidelity Acitve Search

Quan Nguyen, Arghavan Modiri, Roman Garnett; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8109-8118

Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks

Quynh Nguyen, Marco Mondelli, Guido F Montufar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8119-8129

Temporal Predictive Coding For Model-Based Planning In Latent Space

Tung D Nguyen, Rui Shu, Tuan Pham, Hung Bui, Stefano Ermon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8130-8139

Differentially Private Densest Subgraph Detection

Dung Nguyen, Anil Vullikanti; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8140-8151

Data Augmentation for Meta-Learning

Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8152-8161

Improved Denoising Diffusion Probabilistic Models

Alexander Quinn Nichol, Prafulla Dhariwal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8162-8171

Smooth $p$-Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications

Sloan Nietert, Ziv Goldfeld, Kengo Kato; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8172-8183

AdaXpert: Adapting Neural Architecture for Growing Data

Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8184-8194

Asynchronous Decentralized Optimization With Implicit Stochastic Variance Reduction

Kenta Niwa, Guoqiang Zhang, W. Bastiaan Kleijn, Noboru Harada, Hiroshi Sawada, Akinori Fujino; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8195-8204

WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points

Albert No, Taeho Yoon, Kwon Sehyun, Ernest K Ryu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8205-8215

The Impact of Record Linkage on Learning from Feature Partitioned Data

Richard Nock, Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Jakub Nabaglo, Giorgio Patrini, Guillaume Smith, Brian Thorne; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8216-8226

Accuracy, Interpretability, and Differential Privacy via Explainable Boosting

Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8227-8237

Posterior Value Functions: Hindsight Baselines for Policy Gradient Methods

Chris Nota, Philip Thomas, Bruno C. Da Silva; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8238-8247

Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes

Sebastian W Ober, Laurence Aitchison; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8248-8259

Regularizing towards Causal Invariance: Linear Models with Proxies

Michael Oberst, Nikolaj Thams, Jonas Peters, David Sontag; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8260-8270

Sparsity-Agnostic Lasso Bandit

Min-Hwan Oh, Garud Iyengar, Assaf Zeevi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8271-8280

Autoencoder Image Interpolation by Shaping the Latent Space

Alon Oring, Zohar Yakhini, Yacov Hel-Or; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8281-8290

Generalization Guarantees for Neural Architecture Search with Train-Validation Split

Samet Oymak, Mingchen Li, Mahdi Soltanolkotabi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8291-8301

Vector Quantized Models for Planning

Sherjil Ozair, Yazhe Li, Ali Razavi, Ioannis Antonoglou, Aaron Van Den Oord, Oriol Vinyals; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8302-8313

Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling

Ozan Özdenizci, Robert Legenstein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8314-8324

Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics

Avik Pal, Yingbo Ma, Viral Shah, Christopher V Rackauckas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8325-8335

RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting

Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8336-8348

Inference for Network Regression Models with Community Structure

Mengjie Pan, Tyler Mccormick, Bailey Fosdick; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8349-8358

Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification

Bo Pang, Ying Nian Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8359-8370

Leveraging Good Representations in Linear Contextual Bandits

Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8371-8380

Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data

Sung Woo Park, Junseok Kwon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8381-8390

Unsupervised Representation Learning via Neural Activation Coding

Yookoon Park, Sangho Lee, Gunhee Kim, David Blei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8391-8400

Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression

Junhyung Park, Uri Shalit, Bernhard Schölkopf, Krikamol Muandet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8401-8412

Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data Generation

Sung Woo Park, Dong Wook Shu, Junseok Kwon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8413-8421

Optimal Counterfactual Explanations in Tree Ensembles

Axel Parmentier, Thibaut Vidal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8422-8431

PHEW : Constructing Sparse Networks that Learn Fast and Generalize Well without Training Data

Shreyas Malakarjun Patil, Constantine Dovrolis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8432-8442

CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints

Anselm Paulus, Michal Rolinek, Vit Musil, Brandon Amos, Georg Martius; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8443-8453

Ensemble Bootstrapping for Q-Learning

Oren Peer, Chen Tessler, Nadav Merlis, Ron Meir; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8454-8463

Homomorphic Sensing: Sparsity and Noise

Liangzu Peng, Boshi Wang, Manolis Tsakiris; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8464-8475

How could Neural Networks understand Programs?

Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8476-8486

Privacy-Preserving Video Classification with Convolutional Neural Networks

Sikha Pentyala, Rafael Dowsley, Martine De Cock; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8487-8499

Rissanen Data Analysis: Examining Dataset Characteristics via Description Length

Ethan Perez, Douwe Kiela, Kyunghyun Cho; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8500-8513

Modelling Behavioural Diversity for Learning in Open-Ended Games

Nicolas Perez-Nieves, Yaodong Yang, Oliver Slumbers, David H Mguni, Ying Wen, Jun Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8514-8524

From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization

Julien Perolat, Remi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro Ortega, Neil Burch, Thomas Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8525-8535

Spectral Smoothing Unveils Phase Transitions in Hierarchical Variational Autoencoders

Adeel Pervez, Efstratios Gavves; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8536-8545

Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision

Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8546-8555

Megaverse: Simulating Embodied Agents at One Million Experiences per Second

Aleksei Petrenko, Erik Wijmans, Brennan Shacklett, Vladlen Koltun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8556-8566

Towards Practical Mean Bounds for Small Samples

My Phan, Philip Thomas, Erik Learned-Miller; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8567-8576

DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs

Vincent Plassier, Maxime Vono, Alain Durmus, Eric Moulines; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8577-8587

GeomCA: Geometric Evaluation of Data Representations

Petra Poklukar, Anastasiia Varava, Danica Kragic; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8588-8598

Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech

Vadim Popov, Ivan Vovk, Vladimir Gogoryan, Tasnima Sadekova, Mikhail Kudinov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8599-8608

Bias-Free Scalable Gaussian Processes via Randomized Truncations

Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P Cunningham; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8609-8619

Dense for the Price of Sparse: Improved Performance of Sparsely Initialized Networks via a Subspace Offset

Ilan Price, Jared Tanner; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8620-8629

BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining

Weizhen Qi, Yeyun Gong, Jian Jiao, Yu Yan, Weizhu Chen, Dayiheng Liu, Kewen Tang, Houqiang Li, Jiusheng Chen, Ruofei Zhang, Ming Zhou, Nan Duan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8630-8639

A Probabilistic Approach to Neural Network Pruning

Xin Qian, Diego Klabjan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8640-8649

Global Prosody Style Transfer Without Text Transcriptions

Kaizhi Qian, Yang Zhang, Shiyu Chang, Jinjun Xiong, Chuang Gan, David Cox, Mark Hasegawa-Johnson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8650-8660

Efficient Differentiable Simulation of Articulated Bodies

Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C Lin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8661-8671

Oneshot Differentially Private Top-k Selection

Gang Qiao, Weijie Su, Li Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8672-8681

Density Constrained Reinforcement Learning

Zengyi Qin, Yuxiao Chen, Chuchu Fan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8682-8692

Budgeted Heterogeneous Treatment Effect Estimation

Tian Qin, Tian-Zuo Wang, Zhi-Hua Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8693-8702

Neural Transformation Learning for Deep Anomaly Detection Beyond Images

Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8703-8714

Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions

Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8715-8725

Optimization Planning for 3D ConvNets

Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Tao Mei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8726-8736

On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game

Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8737-8747

Learning Transferable Visual Models From Natural Language Supervision

Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8748-8763

A General Framework For Detecting Anomalous Inputs to DNN Classifiers

Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8764-8775

Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning

Muhammad A Rahman, Niklas Hopner, Filippos Christianos, Stefano V Albrecht; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8776-8786

Decoupling Value and Policy for Generalization in Reinforcement Learning

Roberta Raileanu, Rob Fergus; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8787-8798

Hierarchical Clustering of Data Streams: Scalable Algorithms and Approximation Guarantees

Anand Rajagopalan, Fabio Vitale, Danny Vainstein, Gui Citovsky, Cecilia M Procopiuc, Claudio Gentile; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8799-8809

Differentially Private Sliced Wasserstein Distance

Alain Rakotomamonjy, Ralaivola Liva; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8810-8820

Zero-Shot Text-to-Image Generation

Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8821-8831

End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series

Syama Sundar Rangapuram, Lucien D Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8832-8843

MSA Transformer

Roshan M Rao, Jason Liu, Robert Verkuil, Joshua Meier, John Canny, Pieter Abbeel, Tom Sercu, Alexander Rives; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8844-8856

Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting

Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8857-8868

Generative Particle Variational Inference via Estimation of Functional Gradients

Neale Ratzlaff, Qinxun Bai, Li Fuxin, Wei Xu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8869-8879

Enhancing Robustness of Neural Networks through Fourier Stabilization

Netanel Raviv, Aidan Kelley, Minzhe Guo, Yevgeniy Vorobeychik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8880-8889

Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces

Ankit Singh Rawat, Aditya K Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix Yu, Sashank Reddi, Sanjiv Kumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8890-8901

Cross-domain Imitation from Observations

Dripta S. Raychaudhuri, Sujoy Paul, Jeroen Vanbaar, Amit K. Roy-Chowdhury; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8902-8912

Implicit Regularization in Tensor Factorization

Noam Razin, Asaf Maman, Nadav Cohen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8913-8924

Align, then memorise: the dynamics of learning with feedback alignment

Maria Refinetti, Stéphane D’Ascoli, Ruben Ohana, Sebastian Goldt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8925-8935

Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed

Maria Refinetti, Sebastian Goldt, Florent Krzakala, Lenka Zdeborova; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8936-8947

Sharf: Shape-conditioned Radiance Fields from a Single View

Konstantinos Rematas, Ricardo Martin-Brualla, Vittorio Ferrari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8948-8958

LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs

Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, Denny Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8959-8970

Interpreting and Disentangling Feature Components of Various Complexity from DNNs

Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8971-8981

Integrated Defense for Resilient Graph Matching

Jiaxiang Ren, Zijie Zhang, Jiayin Jin, Xin Zhao, Sixing Wu, Yang Zhou, Yelong Shen, Tianshi Che, Ruoming Jin, Dejing Dou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8982-8997

Solving high-dimensional parabolic PDEs using the tensor train format

Lorenz Richter, Leon Sallandt, Nikolas Nüsken; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8998-9009

Best Arm Identification in Graphical Bilinear Bandits

Geovani Rizk, Albert Thomas, Igor Colin, Rida Laraki, Yann Chevaleyre; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9010-9019

Principled Simplicial Neural Networks for Trajectory Prediction

T. Mitchell Roddenberry, Nicholas Glaze, Santiago Segarra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9020-9029

On Linear Identifiability of Learned Representations

Geoffrey Roeder, Luke Metz, Durk Kingma; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9030-9039

Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data

Esther Rolf, Theodora T Worledge, Benjamin Recht, Michael Jordan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9040-9051

TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL

Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9052-9063

Discretization Drift in Two-Player Games

Mihaela C Rosca, Yan Wu, Benoit Dherin, David Barrett; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9064-9074

On the Predictability of Pruning Across Scales

Jonathan S Rosenfeld, Jonathan Frankle, Michael Carbin, Nir Shavit; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9075-9083

Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement

Andrew Ross, Finale Doshi-Velez; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9084-9094

Simultaneous Similarity-based Self-Distillation for Deep Metric Learning

Karsten Roth, Timo Milbich, Bjorn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9095-9106

Multi-group Agnostic PAC Learnability

Guy N Rothblum, Gal Yona; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9107-9115

PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees

Jonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9116-9126

An Algorithm for Stochastic and Adversarial Bandits with Switching Costs

Chloé Rouyer, Yevgeny Seldin, Nicolò Cesa-Bianchi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9127-9135

Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding

Yangjun Ruan, Karen Ullrich, Daniel S Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris Maddison; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9136-9147

On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes

Tim G. J. Rudner, Oscar Key, Yarin Gal, Tom Rainforth; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9148-9156

Tilting the playing field: Dynamical loss functions for machine learning

Miguel Ruiz-Garcia, Ge Zhang, Samuel S Schoenholz, Andrea J. Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9157-9167

UnICORNN: A recurrent model for learning very long time dependencies

T. Konstantin Rusch, Siddhartha Mishra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9168-9178

Simple and Effective VAE Training with Calibrated Decoders

Oleh Rybkin, Kostas Daniilidis, Sergey Levine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9179-9189

Model-Based Reinforcement Learning via Latent-Space Collocation

Oleh Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9190-9201

Training Data Subset Selection for Regression with Controlled Generalization Error

Durga S, Rishabh Iyer, Ganesh Ramakrishnan, Abir De; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9202-9212

Unsupervised Part Representation by Flow Capsules

Sara Sabour, Andrea Tagliasacchi, Soroosh Yazdani, Geoffrey Hinton, David J Fleet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9213-9223

Stochastic Sign Descent Methods: New Algorithms and Better Theory

Mher Safaryan, Peter Richtarik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9224-9234

Adversarial Dueling Bandits

Aadirupa Saha, Tomer Koren, Yishay Mansour; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9235-9244

Dueling Convex Optimization

Aadirupa Saha, Tomer Koren, Yishay Mansour; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9245-9254

Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization

Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9255-9264

Asymptotics of Ridge Regression in Convolutional Models

Mojtaba Sahraee-Ardakan, Tung Mai, Anup Rao, Ryan A. Rossi, Sundeep Rangan, Alyson K Fletcher; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9265-9275

Momentum Residual Neural Networks

Michael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9276-9287

Meta-Learning Bidirectional Update Rules

Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Tom Madams, Andrew Jackson, Blaise Agüera Y Arcas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9288-9300

Recomposing the Reinforcement Learning Building Blocks with Hypernetworks

Elad Sarafian, Shai Keynan, Sarit Kraus; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9301-9312

Towards Understanding Learning in Neural Networks with Linear Teachers

Roei Sarussi, Alon Brutzkus, Amir Globerson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9313-9322

E(n) Equivariant Graph Neural Networks

Vı́ctor Garcia Satorras, Emiel Hoogeboom, Max Welling; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9323-9332

A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning

Nikunj Saunshi, Arushi Gupta, Wei Hu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9333-9343

Low-Rank Sinkhorn Factorization

Meyer Scetbon, Marco Cuturi, Gabriel Peyré; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9344-9354

Linear Transformers Are Secretly Fast Weight Programmers

Imanol Schlag, Kazuki Irie, Jürgen Schmidhuber; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9355-9366

Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers

Robin M Schmidt, Frank Schneider, Philipp Hennig; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9367-9376

Equivariant message passing for the prediction of tensorial properties and molecular spectra

Kristof Schütt, Oliver Unke, Michael Gastegger; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9377-9388

Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks

Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P Dickerson, Tom Goldstein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9389-9398

Connecting Sphere Manifolds Hierarchically for Regularization

Damien Scieur, Youngsung Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9399-9409

Learning Intra-Batch Connections for Deep Metric Learning

Jenny Denise Seidenschwarz, Ismail Elezi, Laura Leal-Taixé; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9410-9421

Top-k eXtreme Contextual Bandits with Arm Hierarchy

Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel N Hill, Inderjit S. Dhillon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9422-9433

Pure Exploration and Regret Minimization in Matching Bandits

Flore Sentenac, Jialin Yi, Clement Calauzenes, Vianney Perchet, Milan Vojnovic; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9434-9442

State Entropy Maximization with Random Encoders for Efficient Exploration

Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9443-9454

Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems

Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause, Maryam Kamgarpour; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9455-9464

RRL: Resnet as representation for Reinforcement Learning

Rutav M Shah, Vikash Kumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9465-9476

Equivariant Networks for Pixelized Spheres

Mehran Shakerinava, Siamak Ravanbakhsh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9477-9488

Personalized Federated Learning using Hypernetworks

Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9489-9502

On the Power of Localized Perceptron for Label-Optimal Learning of Halfspaces with Adversarial Noise

Jie Shen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9503-9514

Sample-Optimal PAC Learning of Halfspaces with Malicious Noise

Jie Shen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9515-9524

Backdoor Scanning for Deep Neural Networks through K-Arm Optimization

Guangyu Shen, Yingqi Liu, Guanhong Tao, Shengwei An, Qiuling Xu, Siyuan Cheng, Shiqing Ma, Xiangyu Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9525-9536

State Relevance for Off-Policy Evaluation

Simon P Shen, Yecheng Ma, Omer Gottesman, Finale Doshi-Velez; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9537-9546

SparseBERT: Rethinking the Importance Analysis in Self-attention

Han Shi, Jiahui Gao, Xiaozhe Ren, Hang Xu, Xiaodan Liang, Zhenguo Li, James Tin-Yau Kwok; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9547-9557

Learning Gradient Fields for Molecular Conformation Generation

Chence Shi, Shitong Luo, Minkai Xu, Jian Tang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9558-9568

Segmenting Hybrid Trajectories using Latent ODEs

Ruian Shi, Quaid Morris; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9569-9579

Deeply-Debiased Off-Policy Interval Estimation

Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9580-9591

GANMEX: One-vs-One Attributions using GAN-based Model Explainability

Sheng-Min Shih, Pin-Ju Tien, Zohar Karnin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9592-9602

Large-Scale Meta-Learning with Continual Trajectory Shifting

Jaewoong Shin, Hae Beom Lee, Boqing Gong, Sung Ju Hwang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9603-9613

AGENT: A Benchmark for Core Psychological Reasoning

Tianmin Shu, Abhishek Bhandwaldar, Chuang Gan, Kevin Smith, Shari Liu, Dan Gutfreund, Elizabeth Spelke, Joshua Tenenbaum, Tomer Ullman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9614-9625

Zoo-Tuning: Adaptive Transfer from A Zoo of Models

Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9626-9637

Aggregating From Multiple Target-Shifted Sources

Changjian Shui, Zijian Li, Jiaqi Li, Christian Gagné, Charles X Ling, Boyu Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9638-9648

Testing Group Fairness via Optimal Transport Projections

Nian Si, Karthyek Murthy, Jose Blanchet, Viet Anh Nguyen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9649-9659

On Characterizing GAN Convergence Through Proximal Duality Gap

Sahil Sidheekh, Aroof Aimen, Narayanan C Krishnan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9660-9670

A Precise Performance Analysis of Support Vector Regression

Houssem Sifaou, Abla Kammoun, Mohamed-Slim Alouini; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9671-9680

Directed Graph Embeddings in Pseudo-Riemannian Manifolds

Aaron Sim, Maciej L Wiatrak, Angus Brayne, Paidi Creed, Saee Paliwal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9681-9690

Collaborative Bayesian Optimization with Fair Regret

Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9691-9701

Dynamic Planning and Learning under Recovering Rewards

David Simchi-Levi, Zeyu Zheng, Feng Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9702-9711

PopSkipJump: Decision-Based Attack for Probabilistic Classifiers

Carl-Johann Simon-Gabriel, Noman Ahmed Sheikh, Andreas Krause; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9712-9721

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clement Hongler, Wulfram Gerstner, Johanni Brea; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9722-9732

Flow-based Attribution in Graphical Models: A Recursive Shapley Approach

Raghav Singal, George Michailidis, Hoiyi Ng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9733-9743

Structured World Belief for Reinforcement Learning in POMDP

Gautam Singh, Skand Peri, Junghyun Kim, Hyunseok Kim, Sungjin Ahn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9744-9755

Skew Orthogonal Convolutions

Sahil Singla, Soheil Feizi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9756-9766

Multi-Task Reinforcement Learning with Context-based Representations

Shagun Sodhani, Amy Zhang, Joelle Pineau; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9767-9779

Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks

Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm H Van Seijen, Mehdi Fatemi, Honglak Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9780-9790

Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving

Yang Song, Chenlin Meng, Renjie Liao, Stefano Ermon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9791-9800

PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration

Yuda Song, Wen Sun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9801-9811

Fast Sketching of Polynomial Kernels of Polynomial Degree

Zhao Song, David Woodruff, Zheng Yu, Lichen Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9812-9823

Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums

Chaobing Song, Stephen J Wright, Jelena Diakonikolas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9824-9834

Oblivious Sketching-based Central Path Method for Linear Programming

Zhao Song, Zheng Yu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9835-9847

Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning

Sumedh A Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9848-9858

Decomposed Mutual Information Estimation for Contrastive Representation Learning

Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoff Gordon, Philip Bachman, Remi Tachet Des Combes; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9859-9869

Decoupling Representation Learning from Reinforcement Learning

Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9870-9879

K-shot NAS: Learnable Weight-Sharing for NAS with K-shot Supernets

Xiu Su, Shan You, Mingkai Zheng, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9880-9890

More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method

Kazuya Sugiyama, Vo Nguyen Le Duy, Ichiro Takeuchi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9891-9901

Not All Memories are Created Equal: Learning to Forget by Expiring

Sainbayar Sukhbaatar, Da Ju, Spencer Poff, Stephen Roller, Arthur Szlam, Jason Weston, Angela Fan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9902-9912

Nondeterminism and Instability in Neural Network Optimization

Cecilia Summers, Michael J. Dinneen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9913-9922

AutoSampling: Search for Effective Data Sampling Schedules

Ming Sun, Haoxuan Dou, Baopu Li, Junjie Yan, Wanli Ouyang, Lei Cui; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9923-9933

What Makes for End-to-End Object Detection?

Peize Sun, Yi Jiang, Enze Xie, Wenqi Shao, Zehuan Yuan, Changhu Wang, Ping Luo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9934-9944

DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning

Wei-Fang Sun, Cheng-Kuang Lee, Chun-Yi Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9945-9954

Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition

Shengyang Sun, Jiaxin Shi, Andrew Gordon Gordon Wilson, Roger B Grosse; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9955-9965

Reasoning Over Virtual Knowledge Bases With Open Predicate Relations

Haitian Sun, Patrick Verga, Bhuwan Dhingra, Ruslan Salakhutdinov, William W Cohen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9966-9977

PAC-Learning for Strategic Classification

Ravi Sundaram, Anil Vullikanti, Haifeng Xu, Fan Yao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9978-9988

Reinforcement Learning for Cost-Aware Markov Decision Processes

Wesley Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David Kraemer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9989-9999

Model-Targeted Poisoning Attacks with Provable Convergence

Fnu Suya, Saeed Mahloujifar, Anshuman Suri, David Evans, Yuan Tian; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10000-10010

Generalization Error Bound for Hyperbolic Ordinal Embedding

Atsushi Suzuki, Atsushi Nitanda, Jing Wang, Linchuan Xu, Kenji Yamanishi, Marc Cavazza; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10011-10021

Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap

Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Steven Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10022-10032

Parallel tempering on optimized paths

Saifuddin Syed, Vittorio Romaniello, Trevor Campbell, Alexandre Bouchard-Cote; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10033-10042

Robust Representation Learning via Perceptual Similarity Metrics

Saeid A Taghanaki, Kristy Choi, Amir Hosein Khasahmadi, Anirudh Goyal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10043-10053

DriftSurf: Stable-State / Reactive-State Learning under Concept Drift

Ashraf Tahmasbi, Ellango Jothimurugesan, Srikanta Tirthapura, Phillip B Gibbons; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10054-10064

Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training

Kai Sheng Tai, Peter D Bailis, Gregory Valiant; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10065-10075

Approximation Theory Based Methods for RKHS Bandits

Sho Takemori, Masahiro Sato; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10076-10085

Supervised Tree-Wasserstein Distance

Yuki Takezawa, Ryoma Sato, Makoto Yamada; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10086-10095

EfficientNetV2: Smaller Models and Faster Training

Mingxing Tan, Quoc Le; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10096-10106

SGA: A Robust Algorithm for Partial Recovery of Tree-Structured Graphical Models with Noisy Samples

Anshoo Tandon, Aldric Han, Vincent Tan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10107-10117

1-bit Adam: Communication Efficient Large-Scale Training with Adam’s Convergence Speed

Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10118-10129

Taylor Expansion of Discount Factors

Yunhao Tang, Mark Rowland, Remi Munos, Michal Valko; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10130-10140

REPAINT: Knowledge Transfer in Deep Reinforcement Learning

Yunzhe Tao, Sahika Genc, Jonathan Chung, Tao Sun, Sunil Mallya; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10141-10152

Understanding the Dynamics of Gradient Flow in Overparameterized Linear models

Salma Tarmoun, Guilherme Franca, Benjamin D Haeffele, Rene Vidal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10153-10161

Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts

Bahar Taskesen, Man-Chung Yue, Jose Blanchet, Daniel Kuhn, Viet Anh Nguyen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10162-10172

A Language for Counterfactual Generative Models

Zenna Tavares, James Koppel, Xin Zhang, Ria Das, Armando Solar-Lezama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10173-10182

Synthesizer: Rethinking Self-Attention for Transformer Models

Yi Tay, Dara Bahri, Donald Metzler, Da-Cheng Juan, Zhe Zhao, Che Zheng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10183-10192

OmniNet: Omnidirectional Representations from Transformers

Yi Tay, Mostafa Dehghani, Vamsi Aribandi, Jai Gupta, Philip M Pham, Zhen Qin, Dara Bahri, Da-Cheng Juan, Donald Metzler; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10193-10202

T-SCI: A Two-Stage Conformal Inference Algorithm with Guaranteed Coverage for Cox-MLP

Jiaye Teng, Zeren Tan, Yang Yuan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10203-10213

Moreau-Yosida $f$-divergences

Dávid Terjék; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10214-10224

Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers

Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C Mozer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10225-10235

Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism

Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael Jordan, Ken Goldberg, Joseph Gonzalez; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10236-10246

Monte Carlo Variational Auto-Encoders

Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10247-10257

Efficient Generative Modelling of Protein Structure Fragments using a Deep Markov Model

Christian B Thygesen, Christian Skjødt Steenmans, Ahmad Salim Al-Sibahi, Lys Sanz Moreta, Anders Bundgård Sørensen, Thomas Hamelryck; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10258-10267

Understanding self-supervised learning dynamics without contrastive pairs

Yuandong Tian, Xinlei Chen, Surya Ganguli; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10268-10278

Online Learning in Unknown Markov Games

Yi Tian, Yuanhao Wang, Tiancheng Yu, Suvrit Sra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10279-10288

BORE: Bayesian Optimization by Density-Ratio Estimation

Louis C Tiao, Aaron Klein, Matthias W Seeger, Edwin V. Bonilla, Cedric Archambeau, Fabio Ramos; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10289-10300

Nonparametric Decomposition of Sparse Tensors

Conor Tillinghast, Shandian Zhe; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10301-10311

Probabilistic Programs with Stochastic Conditioning

David Tolpin, Yuan Zhou, Tom Rainforth, Hongseok Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10312-10323

Deep Continuous Networks

Nergis Tomen, Silvia-Laura Pintea, Jan Van Gemert; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10324-10335

Diffusion Earth Mover’s Distance and Distribution Embeddings

Alexander Y Tong, Guillaume Huguet, Amine Natik, Kincaid Macdonald, Manik Kuchroo, Ronald Coifman, Guy Wolf, Smita Krishnaswamy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10336-10346

Training data-efficient image transformers & distillation through attention

Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, Herve Jegou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10347-10357

Conservative Objective Models for Effective Offline Model-Based Optimization

Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10358-10368

Sparse within Sparse Gaussian Processes using Neighbor Information

Gia-Lac Tran, Dimitrios Milios, Pietro Michiardi, Maurizio Filippone; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10369-10378

SMG: A Shuffling Gradient-Based Method with Momentum

Trang H Tran, Lam M Nguyen, Quoc Tran-Dinh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10379-10389

Bayesian Optimistic Optimisation with Exponentially Decaying Regret

Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10390-10400

On Disentangled Representations Learned from Correlated Data

Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10401-10412

A New Formalism, Method and Open Issues for Zero-Shot Coordination

Johannes Treutlein, Michael Dennis, Caspar Oesterheld, Jakob Foerster; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10413-10423

Learning a Universal Template for Few-shot Dataset Generalization

Eleni Triantafillou, Hugo Larochelle, Richard Zemel, Vincent Dumoulin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10424-10433

Provable Meta-Learning of Linear Representations

Nilesh Tripuraneni, Chi Jin, Michael Jordan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10434-10443

Cumulants of Hawkes Processes are Robust to Observation Noise

William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10444-10454

PixelTransformer: Sample Conditioned Signal Generation

Shubham Tulsiani, Abhinav Gupta; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10455-10464

A Framework for Private Matrix Analysis in Sliding Window Model

Jalaj Upadhyay, Sarvagya Upadhyay; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10465-10475

Fast Projection Onto Convex Smooth Constraints

Ilnura Usmanova, Maryam Kamgarpour, Andreas Krause, Kfir Levy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10476-10486

SGLB: Stochastic Gradient Langevin Boosting

Aleksei Ustimenko, Liudmila Prokhorenkova; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10487-10496

LTL2Action: Generalizing LTL Instructions for Multi-Task RL

Pashootan Vaezipoor, Andrew C Li, Rodrigo A Toro Icarte, Sheila A. Mcilraith; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10497-10508

Active Deep Probabilistic Subsampling

Hans Van Gorp, Iris Huijben, Bastiaan S Veeling, Nicola Pezzotti, Ruud J. G. Van Sloun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10509-10518

CURI: A Benchmark for Productive Concept Learning Under Uncertainty

Ramakrishna Vedantam, Arthur Szlam, Maximillian Nickel, Ari Morcos, Brenden M Lake; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10519-10529

Towards Domain-Agnostic Contrastive Learning

Vikas Verma, Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc Le; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10530-10541

Sparsifying Networks via Subdifferential Inclusion

Sagar Verma, Jean-Christophe Pesquet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10542-10552

Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies

Paul Vicol, Luke Metz, Jascha Sohl-Dickstein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10553-10563

Online Graph Dictionary Learning

Cédric Vincent-Cuaz, Titouan Vayer, Rémi Flamary, Marco Corneli, Nicolas Courty; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10564-10574

Neuro-algorithmic Policies Enable Fast Combinatorial Generalization

Marin Vlastelica, Michal Rolinek, Georg Martius; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10575-10585

Efficient Training of Robust Decision Trees Against Adversarial Examples

Daniël Vos, Sicco Verwer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10586-10595

Object Segmentation Without Labels with Large-Scale Generative Models

Andrey Voynov, Stanislav Morozov, Artem Babenko; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10596-10606

Principal Component Hierarchy for Sparse Quadratic Programs

Robbie Vreugdenhil, Viet Anh Nguyen, Armin Eftekhari, Peyman Mohajerin Esfahani; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10607-10616

Whitening and Second Order Optimization Both Make Information in the Dataset Unusable During Training, and Can Reduce or Prevent Generalization

Neha Wadia, Daniel Duckworth, Samuel S Schoenholz, Ethan Dyer, Jascha Sohl-Dickstein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10617-10629

Safe Reinforcement Learning Using Advantage-Based Intervention

Nolan C Wagener, Byron Boots, Ching-An Cheng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10630-10640

Task-Optimal Exploration in Linear Dynamical Systems

Andrew J Wagenmaker, Max Simchowitz, Kevin Jamieson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10641-10652

Learning and Planning in Average-Reward Markov Decision Processes

Yi Wan, Abhishek Naik, Richard S Sutton; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10653-10662

Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces

Xingchen Wan, Vu Nguyen, Huong Ha, Binxin Ru, Cong Lu, Michael A. Osborne; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10663-10674

Zero-Shot Knowledge Distillation from a Decision-Based Black-Box Model

Zi Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10675-10685

Fairness of Exposure in Stochastic Bandits

Lequn Wang, Yiwei Bai, Wen Sun, Thorsten Joachims; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10686-10696

A Proxy Variable View of Shared Confounding

Yixin Wang, David Blei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10697-10707

Fast Algorithms for Stackelberg Prediction Game with Least Squares Loss

Jiali Wang, He Chen, Rujun Jiang, Xudong Li, Zihao Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10708-10716

Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework

Wenxiao Wang, Minghao Chen, Shuai Zhao, Long Chen, Jinming Hu, Haifeng Liu, Deng Cai, Xiaofei He, Wei Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10717-10726

Explainable Automated Graph Representation Learning with Hyperparameter Importance

Xin Wang, Shuyi Fan, Kun Kuang, Wenwu Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10727-10737

Self-Tuning for Data-Efficient Deep Learning

Ximei Wang, Jinghan Gao, Mingsheng Long, Jianmin Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10738-10748

Label Distribution Learning Machine

Jing Wang, Xin Geng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10749-10759

AlphaNet: Improved Training of Supernets with Alpha-Divergence

Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10760-10771

Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time

Weichen Wang, Jiequn Han, Zhuoran Yang, Zhaoran Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10772-10782

SG-PALM: a Fast Physically Interpretable Tensor Graphical Model

Yu Wang, Alfred Hero; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10783-10793

Deep Generative Learning via Schrödinger Bridge

Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10794-10804

Robust Inference for High-Dimensional Linear Models via Residual Randomization

Y. Samuel Wang, Si Kai Lee, Panos Toulis, Mladen Kolar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10805-10815

A Modular Analysis of Provable Acceleration via Polyak’s Momentum: Training a Wide ReLU Network and a Deep Linear Network

Jun-Kun Wang, Chi-Heng Lin, Jacob D Abernethy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10816-10827

Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method

Peng Wang, Huikang Liu, Zirui Zhou, Anthony Man-Cho So; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10828-10838

ConvexVST: A Convex Optimization Approach to Variance-stabilizing Transformation

Mengfan Wang, Boyu Lyu, Guoqiang Yu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10839-10848

The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks

Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10849-10858

Robust Learning for Data Poisoning Attacks

Yunjuan Wang, Poorya Mianjy, Raman Arora; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10859-10869

SketchEmbedNet: Learning Novel Concepts by Imitating Drawings

Alexander Wang, Mengye Ren, Richard Zemel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10870-10881

Directional Bias Amplification

Angelina Wang, Olga Russakovsky; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10882-10893

An exact solver for the Weston-Watkins SVM subproblem

Yutong Wang, Clayton Scott; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10894-10904

SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II

Xiangjun Wang, Junxiao Song, Penghui Qi, Peng Peng, Zhenkun Tang, Wei Zhang, Weimin Li, Xiongjun Pi, Jujie He, Chao Gao, Haitao Long, Quan Yuan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10905-10915

Quantum algorithms for reinforcement learning with a generative model

Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10916-10926

Matrix Completion with Model-free Weighting

Jiayi Wang, Raymond K. W. Wong, Xiaojun Mao, Kwun Chuen Gary Chan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10927-10936

UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data

Chengyi Wang, Yu Wu, Yao Qian, Kenichi Kumatani, Shujie Liu, Furu Wei, Michael Zeng, Xuedong Huang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10937-10947

Instabilities of Offline RL with Pre-Trained Neural Representation

Ruosong Wang, Yifan Wu, Ruslan Salakhutdinov, Sham Kakade; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10948-10960

Learning to Weight Imperfect Demonstrations

Yunke Wang, Chang Xu, Bo Du, Honglak Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10961-10970

Evolving Attention with Residual Convolutions

Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10971-10980

Guarantees for Tuning the Step Size using a Learning-to-Learn Approach

Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10981-10990

Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation

Haoxiang Wang, Han Zhao, Bo Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10991-11002

Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing

Kaixin Wang, Kuangqi Zhou, Qixin Zhang, Jie Shao, Bryan Hooi, Jiashi Feng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11003-11012

Robust Asymmetric Learning in POMDPs

Andrew Warrington, Jonathan W Lavington, Adam Scibior, Mark Schmidt, Frank Wood; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11013-11023

A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention

Tomoki Watanabe, Paolo Favaro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11024-11034

Decision-Making Under Selective Labels: Optimal Finite-Domain Policies and Beyond

Dennis Wei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11035-11046

Inferring serial correlation with dynamic backgrounds

Song Wei, Yao Xie, Dobromir Rahnev; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11047-11057

Meta-learning Hyperparameter Performance Prediction with Neural Processes

Ying Wei, Peilin Zhao, Junzhou Huang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11058-11067

A Structured Observation Distribution for Generative Biological Sequence Prediction and Forecasting

Eli N Weinstein, Debora Marks; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11068-11079

Thinking Like Transformers

Gail Weiss, Yoav Goldberg, Eran Yahav; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11080-11090

Leveraged Weighted Loss for Partial Label Learning

Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11091-11100

Characterizing the Gap Between Actor-Critic and Policy Gradient

Junfeng Wen, Saurabh Kumar, Ramki Gummadi, Dale Schuurmans; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11101-11111

Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning

Zixin Wen, Yuanzhi Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11112-11122

Keyframe-Focused Visual Imitation Learning

Chuan Wen, Jierui Lin, Jianing Qian, Yang Gao, Dinesh Jayaraman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11123-11133

Learning de-identified representations of prosody from raw audio

Jack Weston, Raphael Lenain, Udeepa Meepegama, Emil Fristed; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11134-11145

Solving Inverse Problems with a Flow-based Noise Model

Jay Whang, Qi Lei, Alex Dimakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11146-11157

Composing Normalizing Flows for Inverse Problems

Jay Whang, Erik Lindgren, Alex Dimakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11158-11169

Which transformer architecture fits my data? A vocabulary bottleneck in self-attention

Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11170-11181

Prediction-Centric Learning of Independent Cascade Dynamics from Partial Observations

Mateusz Wilinski, Andrey Lokhov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11182-11192

Leveraging Language to Learn Program Abstractions and Search Heuristics

Catherine Wong, Kevin M Ellis, Joshua Tenenbaum, Jacob Andreas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11193-11204

Leveraging Sparse Linear Layers for Debuggable Deep Networks

Eric Wong, Shibani Santurkar, Aleksander Madry; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11205-11216

Learning Neural Network Subspaces

Mitchell Wortsman, Maxwell C Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11217-11227

Conjugate Energy-Based Models

Hao Wu, Babak Esmaeili, Michael Wick, Jean-Baptiste Tristan, Jan-Willem Van De Meent; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11228-11239

Making Paper Reviewing Robust to Bid Manipulation Attacks

Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens Van Der Maaten, Kilian Weinberger; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11240-11250

LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning

Yuhuai Wu, Markus N Rabe, Wenda Li, Jimmy Ba, Roger B Grosse, Christian Szegedy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11251-11262

ChaCha for Online AutoML

Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11263-11273

Temporally Correlated Task Scheduling for Sequence Learning

Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11274-11284

Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels

Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11285-11295

On Reinforcement Learning with Adversarial Corruption and Its Application to Block MDP

Tianhao Wu, Yunchang Yang, Simon Du, Liwei Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11296-11306

Generative Video Transformer: Can Objects be the Words?

Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11307-11318

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11319-11328

Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach

Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Junchi Yan, Hongyuan Zha; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11329-11339

Data-efficient Hindsight Off-policy Option Learning

Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala, Noah Siegel, Nicolas Heess, Martin Riedmiller; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11340-11350

A Bit More Bayesian: Domain-Invariant Learning with Uncertainty

Zehao Xiao, Jiayi Shen, Xiantong Zhen, Ling Shao, Cees Snoek; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11351-11361

On the Optimality of Batch Policy Optimization Algorithms

Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvari, Dale Schuurmans; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11362-11371

CRFL: Certifiably Robust Federated Learning against Backdoor Attacks

Chulin Xie, Minghao Chen, Pin-Yu Chen, Bo Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11372-11382

RNNRepair: Automatic RNN Repair via Model-based Analysis

Xiaofei Xie, Wenbo Guo, Lei Ma, Wei Le, Jian Wang, Lingjun Zhou, Yang Liu, Xinyu Xing; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11383-11392

Deep Reinforcement Learning amidst Continual Structured Non-Stationarity

Annie Xie, James Harrison, Chelsea Finn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11393-11403

Batch Value-function Approximation with Only Realizability

Tengyang Xie, Nan Jiang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11404-11413

Interaction-Grounded Learning

Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11414-11423

Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization

Sang Michael Xie, Tengyu Ma, Percy Liang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11424-11435

Learning While Playing in Mean-Field Games: Convergence and Optimality

Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11436-11447

Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization

Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11448-11458

A Hybrid Variance-Reduced Method for Decentralized Stochastic Non-Convex Optimization

Ran Xin, Usman Khan, Soummya Kar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11459-11469

Explore Visual Concept Formation for Image Classification

Shengzhou Xiong, Yihua Tan, Guoyou Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11470-11479

CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee

Tengyu Xu, Yingbin Liang, Guanghui Lan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11480-11491

To be Robust or to be Fair: Towards Fairness in Adversarial Training

Han Xu, Xiaorui Liu, Yaxin Li, Anil Jain, Jiliang Tang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11492-11501

Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold

Wenkai Xu, Takeru Matsuda; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11502-11513

Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives

Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, Kannan Achan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11514-11524

Dash: Semi-Supervised Learning with Dynamic Thresholding

Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yu-Feng Li, Baigui Sun, Hao Li, Rong Jin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11525-11536

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming

Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gomez-Bombarelli, Jian Tang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11537-11547

Self-supervised Graph-level Representation Learning with Local and Global Structure

Minghao Xu, Hang Wang, Bingbing Ni, Hongyu Guo, Jian Tang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11548-11558

Conformal prediction interval for dynamic time-series

Chen Xu, Yao Xie; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11559-11569

Learner-Private Convex Optimization

Jiaming Xu, Kuang Xu, Dana Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11570-11580

Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality

Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11581-11591

Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth

Keyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11592-11602

Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings

Kan Xu, Xuanyi Zhao, Hamsa Bastani, Osbert Bastani; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11603-11612

KNAS: Green Neural Architecture Search

Jingjing Xu, Liang Zhao, Junyang Lin, Rundong Gao, Xu Sun, Hongxia Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11613-11625

Structured Convolutional Kernel Networks for Airline Crew Scheduling

Yassine Yaakoubi, Francois Soumis, Simon Lacoste-Julien; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11626-11636

Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences

Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11637-11647

EL-Attention: Memory Efficient Lossless Attention for Generation

Yu Yan, Jiusheng Chen, Weizhen Qi, Nikhil Bhendawade, Yeyun Gong, Nan Duan, Ruofei Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11648-11658

Link Prediction with Persistent Homology: An Interactive View

Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11659-11669

CATE: Computation-aware Neural Architecture Encoding with Transformers

Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11670-11681

On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Framework

Zeyu Yan, Fei Wen, Rendong Ying, Chao Ma, Peilin Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11682-11692

CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection

Hanshu Yan, Jingfeng Zhang, Gang Niu, Jiashi Feng, Vincent Tan, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11693-11703

Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models

Zitong Yang, Yu Bai, Song Mei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11704-11715

Learning Optimal Auctions with Correlated Valuations from Samples

Chunxue Yang, Xiaohui Bei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11716-11726

Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks

Greg Yang, Edward J. Hu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11727-11737

LARNet: Lie Algebra Residual Network for Face Recognition

Xiaolong Yang, Xiaohong Jia, Dihong Gong, Dong-Ming Yan, Zhifeng Li, Wei Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11738-11750

BASGD: Buffered Asynchronous SGD for Byzantine Learning

Yi-Rui Yang, Wu-Jun Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11751-11761

Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics

Greg Yang, Etai Littwin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11762-11772

Graph Neural Networks Inspired by Classical Iterative Algorithms

Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11773-11783

Representation Matters: Offline Pretraining for Sequential Decision Making

Mengjiao Yang, Ofir Nachum; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11784-11794

Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies

Tsung-Yen Yang, Justinian Rosca, Karthik Narasimhan, Peter J Ramadge; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11795-11807

Voice2Series: Reprogramming Acoustic Models for Time Series Classification

Chao-Han Huck Yang, Yun-Yun Tsai, Pin-Yu Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11808-11819

When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC

Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao, Qingming Huang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11820-11829

Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss

Xue Yang, Junchi Yan, Qi Ming, Wentao Wang, Xiaopeng Zhang, Qi Tian; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11830-11841

Delving into Deep Imbalanced Regression

Yuzhe Yang, Kaiwen Zha, Yingcong Chen, Hao Wang, Dina Katabi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11842-11851

Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural Networks

Yukun Yang, Wenrui Zhang, Peng Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11852-11862

SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks

Lingxiao Yang, Ru-Yuan Zhang, Lida Li, Xiaohua Xie; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11863-11874

HAWQ-V3: Dyadic Neural Network Quantization

Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael Mahoney, Kurt Keutzer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11875-11886

Improving Generalization in Meta-learning via Task Augmentation

Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui () Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11887-11897

Deep Learning for Functional Data Analysis with Adaptive Basis Layers

Junwen Yao, Jonas Mueller, Jane-Ling Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11898-11908

Addressing Catastrophic Forgetting in Few-Shot Problems

Pauching Yap, Hippolyt Ritter, David Barber; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11909-11919

Reinforcement Learning with Prototypical Representations

Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11920-11931

Elementary superexpressive activations

Dmitry Yarotsky; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11932-11940

Break-It-Fix-It: Unsupervised Learning for Program Repair

Michihiro Yasunaga, Percy Liang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11941-11952

Improving Gradient Regularization using Complex-Valued Neural Networks

Eric C Yeats, Yiran Chen, Hai Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11953-11963

Neighborhood Contrastive Learning Applied to Online Patient Monitoring

Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11964-11974

From Local Structures to Size Generalization in Graph Neural Networks

Gilad Yehudai, Ethan Fetaya, Eli Meirom, Gal Chechik, Haggai Maron; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11975-11986

Improved OOD Generalization via Adversarial Training and Pretraing

Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhiming Ma; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11987-11997

Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints

Xinlei Yi, Xiuxian Li, Tao Yang, Lihua Xie, Tianyou Chai, Karl Johansson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11998-12008

Continuous-time Model-based Reinforcement Learning

Cagatay Yildiz, Markus Heinonen, Harri Lähdesmäki; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12009-12018

Distributed Nyström Kernel Learning with Communications

Rong Yin, Weiping Wang, Dan Meng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12019-12028

Path Planning using Neural A* Search

Ryo Yonetani, Tatsunori Taniai, Mohammadamin Barekatain, Mai Nishimura, Asako Kanezaki; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12029-12039

SinIR: Efficient General Image Manipulation with Single Image Reconstruction

Jihyeong Yoo, Qifeng Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12040-12050

Conditional Temporal Neural Processes with Covariance Loss

Boseon Yoo, Jiwoo Lee, Janghoon Ju, Seijun Chung, Soyeon Kim, Jaesik Choi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12051-12061

Adversarial Purification with Score-based Generative Models

Jongmin Yoon, Sung Ju Hwang, Juho Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12062-12072

Federated Continual Learning with Weighted Inter-client Transfer

Jaehong Yoon, Wonyong Jeong, Giwoong Lee, Eunho Yang, Sung Ju Hwang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12073-12086

Autoencoding Under Normalization Constraints

Sangwoong Yoon, Yung-Kyun Noh, Frank Park; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12087-12097

Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient Norm

Taeho Yoon, Ernest K Ryu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12098-12109

Lower-Bounded Proper Losses for Weakly Supervised Classification

Shuhei M Yoshida, Takashi Takenouchi, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12110-12120

Graph Contrastive Learning Automated

Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12121-12132

LogME: Practical Assessment of Pre-trained Models for Transfer Learning

Kaichao You, Yong Liu, Jianmin Wang, Mingsheng Long; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12133-12143

Exponentially Many Local Minima in Quantum Neural Networks

Xuchen You, Xiaodi Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12144-12155

DAGs with No Curl: An Efficient DAG Structure Learning Approach

Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12156-12166

Provably Efficient Algorithms for Multi-Objective Competitive RL

Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12167-12176

Whittle Networks: A Deep Likelihood Model for Time Series

Zhongjie Yu, Fabrizio G Ventola, Kristian Kersting; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12177-12186

Deep Latent Graph Matching

Tianshu Yu, Runzhong Wang, Junchi Yan, Baoxin Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12187-12197

Learning Generalized Intersection Over Union for Dense Pixelwise Prediction

Jiaqian Yu, Jingtao Xu, Yiwei Chen, Weiming Li, Qiang Wang, Byungin Yoo, Jae-Joon Han; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12198-12207

Large Scale Private Learning via Low-rank Reparametrization

Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12208-12218

Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity

Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12219-12229

Neural Tangent Generalization Attacks

Chia-Hung Yuan, Shan-Hung Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12230-12240

On Explainability of Graph Neural Networks via Subgraph Explorations

Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12241-12252

Federated Composite Optimization

Honglin Yuan, Manzil Zaheer, Sashank Reddi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12253-12266

Three Operator Splitting with a Nonconvex Loss Function

Alp Yurtsever, Varun Mangalick, Suvrit Sra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12267-12277

Grey-box Extraction of Natural Language Models

Santiago Zanella-Beguelin, Shruti Tople, Andrew Paverd, Boris Köpf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12278-12286

Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL

Andrea Zanette; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12287-12297

Learning Binary Decision Trees by Argmin Differentiation

Valentina Zantedeschi, Matt Kusner, Vlad Niculae; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12298-12309

Barlow Twins: Self-Supervised Learning via Redundancy Reduction

Jure Zbontar, Li Jing, Ishan Misra, Yann Lecun, Stephane Deny; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12310-12320

You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling

Zhanpeng Zeng, Yunyang Xiong, Sathya Ravi, Shailesh Acharya, Glenn M Fung, Vikas Singh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12321-12332

DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning

Daochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12333-12344

DORO: Distributional and Outlier Robust Optimization

Runtian Zhai, Chen Dan, Zico Kolter, Pradeep Ravikumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12345-12355

Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?

Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron Courville; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12356-12367

Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons

Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12368-12379

Efficient Lottery Ticket Finding: Less Data is More

Zhenyu Zhang, Xuxi Chen, Tianlong Chen, Zhangyang Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12380-12390

Robust Policy Gradient against Strong Data Corruption

Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12391-12401

Near Optimal Reward-Free Reinforcement Learning

Zihan Zhang, Simon Du, Xiangyang Ji; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12402-12412

Bayesian Attention Belief Networks

Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12413-12426

Understanding Failures in Out-of-Distribution Detection with Deep Generative Models

Lily Zhang, Mark Goldstein, Rajesh Ranganath; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12427-12436

Poolingformer: Long Document Modeling with Pooling Attention

Hang Zhang, Yeyun Gong, Yelong Shen, Weisheng Li, Jiancheng Lv, Nan Duan, Weizhu Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12437-12446

Probabilistic Generating Circuits

Honghua Zhang, Brendan Juba, Guy Van Den Broeck; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12447-12457

PAPRIKA: Private Online False Discovery Rate Control

Wanrong Zhang, Gautam Kamath, Rachel Cummings; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12458-12467

Learning from Noisy Labels with No Change to the Training Process

Mingyuan Zhang, Jane Lee, Shivani Agarwal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12468-12478

Progressive-Scale Boundary Blackbox Attack via Projective Gradient Estimation

Jiawei Zhang, Linyi Li, Huichen Li, Xiaolu Zhang, Shuang Yang, Bo Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12479-12490

FOP: Factorizing Optimal Joint Policy of Maximum-Entropy Multi-Agent Reinforcement Learning

Tianhao Zhang, Yueheng Li, Chen Wang, Guangming Xie, Zongqing Lu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12491-12500

Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization

Yivan Zhang, Gang Niu, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12501-12512

Quantile Bandits for Best Arms Identification

Mengyan Zhang, Cheng Soon Ong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12513-12523

Towards Better Robust Generalization with Shift Consistency Regularization

Shufei Zhang, Zhuang Qian, Kaizhu Huang, Qiufeng Wang, Rui Zhang, Xinping Yi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12524-12534

On-Policy Deep Reinforcement Learning for the Average-Reward Criterion

Yiming Zhang, Keith W Ross; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12535-12545

Differentiable Dynamic Quantization with Mixed Precision and Adaptive Resolution

Zhaoyang Zhang, Wenqi Shao, Jinwei Gu, Xiaogang Wang, Ping Luo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12546-12556

iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients

Miao Zhang, Steven W. Su, Shirui Pan, Xiaojun Chang, Ehsan M Abbasnejad, Reza Haffari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12557-12566

Deep Coherent Exploration for Continuous Control

Yijie Zhang, Herke Van Hoof; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12567-12577

Average-Reward Off-Policy Policy Evaluation with Function Approximation

Shangtong Zhang, Yi Wan, Richard S Sutton, Shimon Whiteson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12578-12588

Matrix Sketching for Secure Collaborative Machine Learning

Mengjiao Zhang, Shusen Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12589-12599

MetaCURE: Meta Reinforcement Learning with Empowerment-Driven Exploration

Jin Zhang, Jianhao Wang, Hao Hu, Tong Chen, Yingfeng Chen, Changjie Fan, Chongjie Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12600-12610

World Model as a Graph: Learning Latent Landmarks for Planning

Lunjun Zhang, Ge Yang, Bradly C Stadie; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12611-12620

Breaking the Deadly Triad with a Target Network

Shangtong Zhang, Hengshuai Yao, Shimon Whiteson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12621-12631

Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference

Shumao Zhang, Pengchuan Zhang, Thomas Y Hou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12632-12641

Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation

Qian Zhang, Yilin Zheng, Jean Honorio; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12642-12652

Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity

Zihan Zhang, Yuan Zhou, Xiangyang Ji; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12653-12662

Learning to Rehearse in Long Sequence Memorization

Zhu Zhang, Chang Zhou, Jianxin Ma, Zhijie Lin, Jingren Zhou, Hongxia Yang, Zhou Zhao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12663-12673

Dataset Condensation with Differentiable Siamese Augmentation

Bo Zhao, Hakan Bilen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12674-12685

Joining datasets via data augmentation in the label space for neural networks

Junbo Zhao, Mingfeng Ou, Linji Xue, Yunkai Cui, Sai Wu, Gang Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12686-12696

Calibrate Before Use: Improving Few-shot Performance of Language Models

Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, Sameer Singh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12697-12706

Few-Shot Neural Architecture Search

Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12707-12718

Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks

Xin Zhao, Zeru Zhang, Zijie Zhang, Lingfei Wu, Jiayin Jin, Yang Zhou, Ruoming Jin, Dejing Dou, Da Yan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12719-12735

Fused Acoustic and Text Encoding for Multimodal Bilingual Pretraining and Speech Translation

Renjie Zheng, Junkun Chen, Mingbo Ma, Liang Huang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12736-12746

Two Heads are Better Than One: Hypergraph-Enhanced Graph Reasoning for Visual Event Ratiocination

Wenbo Zheng, Lan Yan, Chao Gou, Fei-Yue Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12747-12760

How Framelets Enhance Graph Neural Networks

Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yuguang Wang, Pietro Lió, Ming Li, Guido Montufar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12761-12771

Probabilistic Sequential Shrinking: A Best Arm Identification Algorithm for Stochastic Bandits with Corruptions

Zixin Zhong, Wang Chi Cheung, Vincent Tan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12772-12781

Towards Distraction-Robust Active Visual Tracking

Fangwei Zhong, Peng Sun, Wenhan Luo, Tingyun Yan, Yizhou Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12782-12792

Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping

Dongruo Zhou, Jiafan He, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12793-12802

Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation

Aurick Zhou, Sergey Levine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12803-12812

Optimal Estimation of High Dimensional Smooth Additive Function Based on Noisy Observations

Fan Zhou, Ping Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12813-12823

Incentivized Bandit Learning with Self-Reinforcing User Preferences

Tianchen Zhou, Jia Liu, Chaosheng Dong, Jingyuan Deng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12824-12834

Towards Defending against Adversarial Examples via Attack-Invariant Features

Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Chunlei Peng, Xinbo Gao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12835-12845

Asymmetric Loss Functions for Learning with Noisy Labels

Xiong Zhou, Xianming Liu, Junjun Jiang, Xin Gao, Xiangyang Ji; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12846-12856

Examining and Combating Spurious Features under Distribution Shift

Chunting Zhou, Xuezhe Ma, Paul Michel, Graham Neubig; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12857-12867

Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm

Mingkang Zhu, Tianlong Chen, Zhangyang Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12868-12877

Data-Free Knowledge Distillation for Heterogeneous Federated Learning

Zhuangdi Zhu, Junyuan Hong, Jiayu Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12878-12889

Spectral vertex sparsifiers and pair-wise spanners over distributed graphs

Chunjiang Zhu, Qinqing Liu, Jinbo Bi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12890-12900

Few-shot Language Coordination by Modeling Theory of Mind

Hao Zhu, Graham Neubig, Yonatan Bisk; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12901-12911

Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels

Zhaowei Zhu, Yiwen Song, Yang Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12912-12923

Commutative Lie Group VAE for Disentanglement Learning

Xinqi Zhu, Chang Xu, Dacheng Tao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12924-12934

Accumulated Decoupled Learning with Gradient Staleness Mitigation for Convolutional Neural Networks

Huiping Zhuang, Zhenyu Weng, Fulin Luo, Toh Kar-Ann, Haizhou Li, Zhiping Lin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12935-12944

Demystifying Inductive Biases for (Beta-)VAE Based Architectures

Dominik Zietlow, Michal Rolinek, Georg Martius; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12945-12954

Recovering AES Keys with a Deep Cold Boot Attack

Itamar Zimerman, Eliya Nachmani, Lior Wolf;