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Volume 130: International Conference on Artificial Intelligence and Statistics, 13-15 April 2021, Virtual

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Editors: Arindam Banerjee, Kenji Fukumizu

[bib][citeproc]

On the Effect of Auxiliary Tasks on Representation Dynamics

Clare Lyle, Mark Rowland, Georg Ostrovski, Will Dabney; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1-9

LassoNet: Neural Networks with Feature Sparsity

Ismael Lemhadri, Feng Ruan, Rob Tibshirani; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:10-18

Projection-Free Optimization on Uniformly Convex Sets

Thomas Kerdreux, Alexandre d’Aspremont, Sebastian Pokutta; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:19-27

Differentiable Greedy Algorithm for Monotone Submodular Maximization: Guarantees, Gradient Estimators, and Applications

Shinsaku Sakaue; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:28-36

Graphical Normalizing Flows

Antoine Wehenkel, Gilles Louppe; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:37-45

One-Round Communication Efficient Distributed M-Estimation

Yajie Bao, Weijia Xiong; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:46-54

CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices

Valerii Likhosherstov, Jared Davis, Krzysztof Choromanski, Adrian Weller; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:55-63

Regularized Policies are Reward Robust

Hisham Husain, Kamil Ciosek, Ryota Tomioka; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:64-72

Semi-Supervised Learning with Meta-Gradient

Taihong Xiao, Xin-Yu Zhang, Haolin Jia, Ming-Ming Cheng, Ming-Hsuan Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:73-81

On Information Gain and Regret Bounds in Gaussian Process Bandits

Sattar Vakili, Kia Khezeli, Victor Picheny; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:82-90

On the proliferation of support vectors in high dimensions

Daniel Hsu, Vidya Muthukumar, Ji Xu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:91-99

Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors

Nikhil Mehta, Kevin Liang, Vinay Kumar Verma, Lawrence Carin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:100-108

A Fast and Robust Method for Global Topological Functional Optimization

Yitzchak Solomon, Alexander Wagner, Paul Bendich; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:109-117

Regression Discontinuity Design under Self-selection

Sida Peng, Yang Ning; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:118-126

Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing Campaigns

Ziping Xu, Amirhossein Meisami, Ambuj Tewari; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:127-135

When OT meets MoM: Robust estimation of Wasserstein Distance

Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d’Alché-Buc; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:136-144

Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint

Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:145-153

Unconstrained MAP Inference, Exponentiated Determinantal Point Processes, and Exponential Inapproximability

Naoto Ohsaka; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:154-162

False Discovery Rates in Biological Networks

Lu Yu, Tobias Kaufmann, Johannes Lederer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:163-171

Fourier Bases for Solving Permutation Puzzles

Horace Pan, Risi Kondor; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:172-180

Accelerating Metropolis-Hastings with Lightweight Inference Compilation

Feynman Liang, Nimar Arora, Nazanin Tehrani, Yucen Li, Michael Tingley, Erik Meijer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:181-189

Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series

Xing Han, Sambarta Dasgupta, Joydeep Ghosh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:190-198

Fully Gap-Dependent Bounds for Multinomial Logit Bandit

Jiaqi Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:199-207

Alternating Direction Method of Multipliers for Quantization

Tianjian Huang, Prajwal Singhania, Maziar Sanjabi, Pabitra Mitra, Meisam Razaviyayn; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:208-216

Online Forgetting Process for Linear Regression Models

Yuantong Li, Chi-Hua Wang, Guang Cheng; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:217-225

A Bayesian nonparametric approach to count-min sketch under power-law data streams

Emanuele Dolera, Stefano Favaro, Stefano Peluchetti; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:226-234

Nonlinear Functional Output Regression: A Dictionary Approach

Dimitri Bouche, Marianne Clausel, François Roueff, Florence d’Alché-Buc; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:235-243

When MAML Can Adapt Fast and How to Assist When It Cannot

Sébastien Arnold, Shariq Iqbal, Fei Sha; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:244-252

Learning Smooth and Fair Representations

Xavier Gitiaux, Huzefa Rangwala; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:253-261

On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification

Tianyi Lin, Zeyu Zheng, Elynn Chen, Marco Cuturi, Michael I. Jordan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:262-270

Contextual Blocking Bandits

Soumya Basu, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:271-279

Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation

Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:280-288

A comparative study on sampling with replacement vs Poisson sampling in optimal subsampling

HaiYing Wang, Jiahui Zou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:289-297

Robust Imitation Learning from Noisy Demonstrations

Voot Tangkaratt, Nontawat Charoenphakdee, Masashi Sugiyama; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:298-306

Online Active Model Selection for Pre-trained Classifiers

Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlaš, Johannes Rausch, Ce Zhang, Andreas Krause; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:307-315

Online Sparse Reinforcement Learning

Botao Hao, Tor Lattimore, Csaba Szepesvari, Mengdi Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:316-324

A Contraction Approach to Model-based Reinforcement Learning

Ting-Han Fan, Peter Ramadge; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:325-333

The Spectrum of Fisher Information of Deep Networks Achieving Dynamical Isometry

Tomohiro Hayase, Ryo Karakida; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:334-342

Benchmarking Simulation-Based Inference

Jan-Matthis Lueckmann, Jan Boelts, David Greenberg, Pedro Goncalves, Jakob Macke; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:343-351

Fisher Auto-Encoders

Khalil Elkhalil, Ali Hasan, Jie Ding, Sina Farsiu, Vahid Tarokh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:352-360

Deep Spectral Ranking

Ilkay Yildiz, Jennifer Dy, Deniz Erdogmus, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Stratis Ioannidis; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:361-369

Tight Regret Bounds for Infinite-armed Linear Contextual Bandits

Yingkai Li, Yining Wang, Xi Chen, Yuan Zhou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:370-378

On the Absence of Spurious Local Minima in Nonlinear Low-Rank Matrix Recovery Problems

Yingjie Bi, Javad Lavaei; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:379-387

Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures

Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan Suykens; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:388-396

Approximate Message Passing with Spectral Initialization for Generalized Linear Models

Marco Mondelli, Ramji Venkataramanan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:397-405

Active Learning with Maximum Margin Sparse Gaussian Processes

Weishi Shi, Qi Yu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:406-414

A Stein Goodness-of-test for Exponential Random Graph Models

Wenkai Xu, Gesine Reinert; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:415-423

The Sample Complexity of Level Set Approximation

François Bachoc, Tommaso Cesari, Sébastien Gerchinovitz; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:424-432

Curriculum Learning by Optimizing Learning Dynamics

Tianyi Zhou, Shengjie Wang, Jeff Bilmes; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:433-441

Approximating Lipschitz continuous functions with GroupSort neural networks

Ugo Tanielian, Gerard Biau; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:442-450

Learning GPLVM with arbitrary kernels using the unscented transformation

Daniel de Souza, Diego Mesquita, João Paulo Gomes, César Lincoln Mattos; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:451-459

Low-Rank Generalized Linear Bandit Problems

Yangyi Lu, Amirhossein Meisami, Ambuj Tewari; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:460-468

On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions

Kai Brügge, Asja Fischer, Christian Igel; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:469-477

Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes

Manuel Haußmann, Sebastian Gerwinn, Andreas Look, Barbara Rakitsch, Melih Kandemir; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:478-486

SONIA: A Symmetric Blockwise Truncated Optimization Algorithm

Majid Jahani, MohammadReza Nazari, Rachael Tappenden, Albert Berahas, Martin Takac; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:487-495

Predictive Power of Nearest Neighbors Algorithm under Random Perturbation

Yue Xing, Qifan Song, Guang Cheng; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:496-504

On the Generalization Properties of Adversarial Training

Yue Xing, Qifan Song, Guang Cheng; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:505-513

Adversarially Robust Estimate and Risk Analysis in Linear Regression

Yue Xing, Ruizhi Zhang, Guang Cheng; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:514-522

Adaptive Approximate Policy Iteration

Botao Hao, Nevena Lazic, Yasin Abbasi-Yadkori, Pooria Joulani, Csaba Szepesvari; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:523-531

Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications

Guillaume Ausset, Stephan Clémencon, François Portier; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:532-540

Foundations of Bayesian Learning from Synthetic Data

Harrison Wilde, Jack Jewson, Sebastian Vollmer, Chris Holmes; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:541-549

Generalization of Quasi-Newton Methods: Application to Robust Symmetric Multisecant Updates

Damien Scieur, Lewis Liu, Thomas Pumir, Nicolas Boumal; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:550-558

Hierarchical Clustering via Sketches and Hierarchical Correlation Clustering

Danny Vainstein, Vaggos Chatziafratis, Gui Citovsky, Anand Rajagopalan, Mohammad Mahdian, Yossi Azar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:559-567

Generalization Bounds for Stochastic Saddle Point Problems

Junyu Zhang, Mingyi Hong, Mengdi Wang, Shuzhong Zhang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:568-576

Learning to Defend by Learning to Attack

Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:577-585

A Deterministic Streaming Sketch for Ridge Regression

Benwei Shi, Jeff Phillips; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:586-594

Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems

Mansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, Ding Zhao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:595-603

On the role of data in PAC-Bayes

Gintare Karolina Dziugaite, Kyle Hsu, Waseem Gharbieh, Gabriel Arpino, Daniel Roy; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:604-612

CADA: Communication-Adaptive Distributed Adam

Tianyi Chen, Ziye Guo, Yuejiao Sun, Wotao Yin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:613-621

Bandit algorithms: Letting go of logarithmic regret for statistical robustness

Kumar Ashutosh, Jayakrishnan Nair, Anmol Kagrecha, Krishna Jagannathan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:622-630

Geometrically Enriched Latent Spaces

Georgios Arvanitidis, Soren Hauberg, Bernhard Schölkopf; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:631-639

Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting

Ilja Kuzborskij, Claire Vernade, Andras Gyorgy, Csaba Szepesvari; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:640-648

Kernel regression in high dimensions: Refined analysis beyond double descent

Fanghui Liu, Zhenyu Liao, Johan Suykens; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:649-657

Self-Concordant Analysis of Generalized Linear Bandits with Forgetting

Yoan Russac, Louis Faury, Olivier Cappé, Aurélien Garivier; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:658-666

Logical Team Q-learning: An approach towards factored policies in cooperative MARL

Lucas Cassano, Ali H. Sayed; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:667-675

Automatic structured variational inference

Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore, Marcel van Gerven; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:676-684

Neural Enhanced Belief Propagation on Factor Graphs

Víctor Garcia Satorras, Max Welling; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:685-693

Predictive Complexity Priors

Eric Nalisnick, Jonathan Gordon, Jose Miguel Hernandez-Lobato; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:694-702

Improving predictions of Bayesian neural nets via local linearization

Alexander Immer, Maciej Korzepa, Matthias Bauer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:703-711

Generalized Spectral Clustering via Gromov-Wasserstein Learning

Samir Chowdhury, Tom Needham; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:712-720

Shapley Flow: A Graph-based Approach to Interpreting Model Predictions

Jiaxuan Wang, Jenna Wiens, Scott Lundberg; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:721-729

Scalable Constrained Bayesian Optimization

David Eriksson, Matthias Poloczek; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:730-738

Sample efficient learning of image-based diagnostic classifiers via probabilistic labels

Roberto Vega, Pouneh Gorji, Zichen Zhang, Xuebin Qin, Abhilash Rakkunedeth, Jeevesh Kapur, Jacob Jaremko, Russell Greiner; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:739-747

Nonparametric Variable Screening with Optimal Decision Stumps

Jason Klusowski, Peter Tian; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:748-756

Sharp Analysis of a Simple Model for Random Forests

Jason Klusowski; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:757-765

Nested Barycentric Coordinate System as an Explicit Feature Map

Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch, Ofir Pele; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:766-774

An Analysis of the Adaptation Speed of Causal Models

Rémi Le Priol, Reza Babanezhad, Yoshua Bengio, Simon Lacoste-Julien; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:775-783

Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints

Robin Vogel, Aurélien Bellet, Stephan Clémençon; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:784-792

Efficient Computation and Analysis of Distributional Shapley Values

Yongchan Kwon, Manuel A. Rivas, James Zou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:793-801

A constrained risk inequality for general losses

John Duchi, Feng Ruan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:802-810

Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms

Tengyu Xu, Yingbin Liang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:811-819

Learning Prediction Intervals for Regression: Generalization and Calibration

Haoxian Chen, Ziyi Huang, Henry Lam, Huajie Qian, Haofeng Zhang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:820-828

Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network

Tianyang Hu, Wenjia Wang, Cong Lin, Guang Cheng; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:829-837

Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning

Chong Liu, Yuqing Zhu, Kamalika Chaudhuri, Yu-Xiang Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:838-846

Multi-Fidelity High-Order Gaussian Processes for Physical Simulation

Zheng Wang, Wei Xing, Robert Kirby, Shandian Zhe; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:847-855

Deep Fourier Kernel for Self-Attentive Point Processes

Shixiang Zhu, Minghe Zhang, Ruyi Ding, Yao Xie; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:856-864

Robustness and scalability under heavy tails, without strong convexity

Matthew Holland; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:865-873

Understanding the wiring evolution in differentiable neural architecture search

Sirui Xie, Shoukang Hu, Xinjiang Wang, Chunxiao Liu, Jianping Shi, Xunying Liu, Dahua Lin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:874-882

Provable Hierarchical Imitation Learning via EM

Zhiyu Zhang, Ioannis Paschalidis; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:883-891

Learning with risk-averse feedback under potentially heavy tails

Matthew Holland, El Mehdi Haress; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:892-900

Parametric Programming Approach for More Powerful and General Lasso Selective Inference

Vo Nguyen Le Duy, Ichiro Takeuchi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:901-909

On the High Accuracy Limitation of Adaptive Property Estimation

Yanjun Han; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:910-918

Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers

Alex Lamb, Anirudh Goyal, Agnieszka Słowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:919-927

Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model

Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed Chi, Qiaozhu Mei; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:928-936

Interpretable Random Forests via Rule Extraction

Clément Bénard, Gérard Biau, Sébastien da Veiga, Erwan Scornet; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:937-945

Regret Minimization for Causal Inference on Large Treatment Space

Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:946-954

Bayesian Model Averaging for Causality Estimation and its Approximation based on Gaussian Scale Mixture Distributions

Shunsuke Horii; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:955-963

Adaptive Sampling for Fast Constrained Maximization of Submodular Functions

Francesco Quinzan, Vanja Doskoc, Andreas Göbel, Tobias Friedrich; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:964-972

Mean-Variance Analysis in Bayesian Optimization under Uncertainty

Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:973-981

Hadamard Wirtinger Flow for Sparse Phase Retrieval

Fan Wu, Patrick Rebeschini; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:982-990

Stochastic Linear Bandits Robust to Adversarial Attacks

Ilija Bogunovic, Arpan Losalka, Andreas Krause, Jonathan Scarlett; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:991-999

ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning

Martin Royer, Frederic Chazal, Clément Levrard, Yuhei Umeda, Yuichi Ike; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1000-1008

Optimizing Percentile Criterion using Robust MDPs

Bahram Behzadian, Reazul Hasan Russel, Marek Petrik, Chin Pang Ho; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1009-1017

On Riemannian Stochastic Approximation Schemes with Fixed Step-Size

Alain Durmus, Pablo Jiménez, Eric Moulines, Salem SAID; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1018-1026

Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy

Onur Teymur, Jackson Gorham, Marina Riabiz, Chris Oates; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1027-1035

Aligning Time Series on Incomparable Spaces

Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Deisenroth; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1036-1044

The Unexpected Deterministic and Universal Behavior of Large Softmax Classifiers

Mohamed El Amine Seddik, Cosme Louart, Romain COUILLET, Mohamed Tamaazousti; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1045-1053

Measure Transport with Kernel Stein Discrepancy

Matthew Fisher, Tui Nolan, Matthew Graham, Dennis Prangle, Chris Oates; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1054-1062

Unifying Clustered and Non-stationary Bandits

Chuanhao Li, Qingyun Wu, Hongning Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1063-1071

A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix

Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1072-1080

Transforming Gaussian Processes With Normalizing Flows

Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1081-1089

Linearly Constrained Gaussian Processes with Boundary Conditions

Markus Lange-Hegermann; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1090-1098

Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings

Jean-Francois Ton, Lucian CHAN, Yee Whye Teh, Dino Sejdinovic; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1099-1107

Top-m identification for linear bandits

Clémence Réda, Emilie Kaufmann, Andrée Delahaye-Duriez; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1108-1116

When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence

Ziwei Guan, Tengyu Xu, Yingbin Liang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1117-1125

Online k-means Clustering

Vincent Cohen-Addad, Benjamin Guedj, Varun Kanade, Guy Rom; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1126-1134

Consistent k-Median: Simpler, Better and Robust

Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1135-1143

Algorithms for Fairness in Sequential Decision Making

Min Wen, Osbert Bastani, Ufuk Topcu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1144-1152

On Learning Continuous Pairwise Markov Random Fields

Abhin Shah, Devavrat Shah, Gregory Wornell; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1153-1161

Abstract Value Iteration for Hierarchical Reinforcement Learning

Kishor Jothimurugan, Osbert Bastani, Rajeev Alur; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1162-1170

Differentially Private Analysis on Graph Streams

Jalaj Upadhyay, Sarvagya Upadhyay, Raman Arora; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1171-1179

Learning with Hyperspherical Uniformity

Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1180-1188

Finding First-Order Nash Equilibria of Zero-Sum Games with the Regularized Nikaido-Isoda Function

Ioannis Tsaknakis, Mingyi Hong; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1189-1197

Latent Derivative Bayesian Last Layer Networks

Joe Watson, Jihao Andreas Lin, Pascal Klink, Joni Pajarinen, Jan Peters; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1198-1206

Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes

Nhuong Nguyen, Toan Nguyen, PHUONG HA NGUYEN, Quoc Tran-Dinh, Lam Nguyen, Marten van Dijk; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1207-1215

Provably Safe PAC-MDP Exploration Using Analogies

Melrose Roderick, Vaishnavh Nagarajan, Zico Kolter; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1216-1224

Maximal Couplings of the Metropolis-Hastings Algorithm

Guanyang Wang, John O’Leary, Pierre Jacob; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1225-1233

Gaming Helps! Learning from Strategic Interactions in Natural Dynamics

Yahav Bechavod, Katrina Ligett, Steven Wu, Juba Ziani; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1234-1242

Goodness-of-Fit Test for Mismatched Self-Exciting Processes

Song Wei, Shixiang Zhu, Minghe Zhang, Yao Xie; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1243-1251

Dominate or Delete: Decentralized Competing Bandits in Serial Dictatorship

Abishek Sankararaman, Soumya Basu, Karthik Abinav Sankararaman; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1252-1260

A Study of Condition Numbers for First-Order Optimization

Charles Guille-Escuret, Manuela Girotti, Baptiste Goujaud, Ioannis Mitliagkas; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1261-1269

Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions

Kartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1270-1278

Differentially Private Online Submodular Maximization

Sebastian Perez Salazar, Rachel Cummings; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1279-1287

Anderson acceleration of coordinate descent

Quentin Bertrand, Mathurin Massias; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1288-1296

Inference in Stochastic Epidemic Models via Multinomial Approximations

Nick Whiteley, Lorenzo Rimella; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1297-1305

Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence

Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1306-1314

SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation

Robert Gower, Othmane Sebbouh, Nicolas Loizou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1315-1323

Stable ResNet

Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1324-1332

Latent variable modeling with random features

Gregory Gundersen, Michael Zhang, Barbara Engelhardt; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1333-1341

Reaping the Benefits of Bundling under High Production Costs

Will Ma, David Simchi-Levi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1342-1350

Momentum Improves Optimization on Riemannian Manifolds

Foivos Alimisis, Antonio Orvieto, Gary Becigneul, Aurelien Lucchi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1351-1359

Quick Streaming Algorithms for Maximization of Monotone Submodular Functions in Linear Time

Alan Kuhnle; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1360-1368

On Data Efficiency of Meta-learning

Maruan Al-Shedivat, Liam Li, Eric Xing, Ameet Talwalkar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1369-1377

Hyperparameter Transfer Learning with Adaptive Complexity

Samuel Horváth, Aaron Klein, Peter Richtarik, Cedric Archambeau; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1378-1386

Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency

Yuyang Deng, Mehrdad Mahdavi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1387-1395

Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits

Avishek Ghosh, Abishek Sankararaman, Ramchandran Kannan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1396-1404

On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression

Jeongyeol Kwon, Nhat Ho, Constantine Caramanis; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1405-1413

Amortized Bayesian Prototype Meta-learning: A New Probabilistic Meta-learning Approach to Few-shot Image Classification

Zhuo Sun, Jijie Wu, Xiaoxu Li, Wenming Yang, Jing-Hao Xue; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1414-1422

Tractable contextual bandits beyond realizability

Sanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1423-1431

Learning User Preferences in Non-Stationary Environments

Wasim Huleihel, Soumyabrata Pal, Ofer Shayevitz; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1432-1440

Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes

Qi Lei, Sai Ganesh Nagarajan, Ioannis Panageas, xiao wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1441-1449

Efficient Statistics for Sparse Graphical Models from Truncated Samples

Arnab Bhattacharyya, Rathin Desai, Sai Ganesh Nagarajan, Ioannis Panageas; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1450-1458

Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations.

Neil Jethani, Mukund Sudarshan, Yindalon Aphinyanaphongs, Rajesh Ranganath; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1459-1467

Feedback Coding for Active Learning

Gregory Canal, Matthieu Bloch, Christopher Rozell; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1468-1476

Shadow Manifold Hamiltonian Monte Carlo

Chris van der Heide, Fred Roosta, Liam Hodgkinson, Dirk Kroese; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1477-1485

Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms

Yilun Zhou, Adithya Renduchintala, Xian Li, Sida Wang, Yashar Mehdad, Asish Ghoshal; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1486-1494

Identification of Matrix Joint Block Diagonalization

Yunfeng Cai, Ping Li; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1495-1503

Understanding Gradient Clipping In Incremental Gradient Methods

Jiang Qian, Yuren Wu, Bojin Zhuang, Shaojun Wang, Jing Xiao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1504-1512

A Variational Information Bottleneck Approach to Multi-Omics Data Integration

Changhee Lee, Mihaela van der Schaar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1513-1521

On the Privacy Properties of GAN-generated Samples

Zinan Lin, Vyas Sekar, Giulia Fanti; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1522-1530

Multitask Bandit Learning Through Heterogeneous Feedback Aggregation

Zhi Wang, Chicheng Zhang, Manish Kumar Singh, Laurel Riek, Kamalika Chaudhuri; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1531-1539

Learning Complexity of Simulated Annealing

Avrim Blum, Chen Dan, Saeed Seddighin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1540-1548

Independent Innovation Analysis for Nonlinear Vector Autoregressive Process

Hiroshi Morioka, Hermanni Hälvä, Aapo Hyvarinen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1549-1557

Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers

Lunjia Hu, Omer Reingold; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1558-1566

Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning

Ming Yin, Yu Bai, Yu-Xiang Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1567-1575

Q-learning with Logarithmic Regret

Kunhe Yang, Lin Yang, Simon Du; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1576-1584

An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling

Qin Ding, Cho-Jui Hsieh, James Sharpnack; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1585-1593

Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization

Congliang Chen, Jiawei Zhang, Li Shen, Peilin Zhao, Zhiquan Luo; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1594-1602

Robust and Private Learning of Halfspaces

Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1603-1611

Minimax Model Learning

Cameron Voloshin, Nan Jiang, Yisong Yue; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1612-1620

On the Faster Alternating Least-Squares for CCA

Zhiqiang Xu, Ping Li; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1621-1629

Exploiting Equality Constraints in Causal Inference

Chi Zhang, Carlos Cinelli, Bryant Chen, Judea Pearl; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1630-1638

Collaborative Classification from Noisy Labels

Lucas Maystre, Nagarjuna Kumarappan, Judith Bütepage, Mounia Lalmas; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1639-1647

Fenchel-Young Losses with Skewed Entropies for Class-posterior Probability Estimation

Han Bao, Masashi Sugiyama; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1648-1656

Maximizing Agreements for Ranking, Clustering and Hierarchical Clustering via MAX-CUT

Vaggos Chatziafratis, Mohammad Mahdian, Sara Ahmadian; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1657-1665

Why did the distribution change?

Kailash Budhathoki, Dominik Janzing, Patrick Bloebaum, Hoiyi Ng; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1666-1674

Non-Volume Preserving Hamiltonian Monte Carlo and No-U-TurnSamplers

Hadi Mohasel Afshar, Rafael Oliveira, Sally Cripps; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1675-1683

Iterative regularization for convex regularizers

Cesare Molinari, Mathurin Massias, Lorenzo Rosasco, Silvia Villa; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1684-1692

Competing AI: How does competition feedback affect machine learning?

Tony Ginart, Eva Zhang, Yongchan Kwon, James Zou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1693-1701

Stability and Risk Bounds of Iterative Hard Thresholding

Xiaotong Yuan, Ping Li; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1702-1710

Novel Change of Measure Inequalities with Applications to PAC-Bayesian Bounds and Monte Carlo Estimation

Yuki Ohnishi, Jean Honorio; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1711-1719

On the Convergence of Gradient Descent in GANs: MMD GAN As a Gradient Flow

Youssef Mroueh, Truyen Nguyen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1720-1728

Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects

Qiming Du, Gérard Biau, Francois Petit, Raphaël Porcher; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1729-1737

Improved Complexity Bounds in Wasserstein Barycenter Problem

Darina Dvinskikh, Daniil Tiapkin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1738-1746

Sparse Algorithms for Markovian Gaussian Processes

William Wilkinson, Arno Solin, Vincent Adam; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1747-1755

Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties

Lisa Schut, Oscar Key, Rory Mc Grath, Luca Costabello, Bogdan Sacaleanu, medb corcoran, Yarin Gal; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1756-1764

Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond

Nina Vesseron, Ievgen Redko, Charlotte Laclau; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1765-1773

All of the Fairness for Edge Prediction with Optimal Transport

Charlotte Laclau, Ievgen Redko, Manvi Choudhary, Christine Largeron; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1774-1782

γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator

Masahiro Fujisawa, Takeshi Teshima, Issei Sato, Masashi Sugiyama; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1783-1791

Understanding and Mitigating Exploding Inverses in Invertible Neural Networks

Jens Behrmann, Paul Vicol, Kuan-Chieh Wang, Roger Grosse, Joern-Henrik Jacobsen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1792-1800

Online probabilistic label trees

Kalina Jasinska-Kobus, Marek Wydmuch, Devanathan Thiruvenkatachari, Krzysztof Dembczynski; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1801-1809

Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms

Alicia Curth, Mihaela van der Schaar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1810-1818

DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation

Frederik Harder, Kamil Adamczewski, Mijung Park; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1819-1827

Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings

Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, Wipf David; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1828-1836

Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations

Simone Rossi, Markus Heinonen, Edwin Bonilla, Zheyang Shen, Maurizio Filippone; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1837-1845

Free-rider Attacks on Model Aggregation in Federated Learning

Yann Fraboni, Richard Vidal, Marco Lorenzi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1846-1854

Reinforcement Learning in Parametric MDPs with Exponential Families

Sayak Ray Chowdhury, Aditya Gopalan, Odalric-Ambrym Maillard; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1855-1863

Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery

Mike Laszkiewicz, Johannes Lederer, Asja Fischer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1864-1872

No-regret Algorithms for Multi-task Bayesian Optimization

Sayak Ray Chowdhury, Aditya Gopalan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1873-1881

Explicit Regularization of Stochastic Gradient Methods through Duality

Anant Raj, Francis Bach; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1882-1890

Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization

Tianyi Liu, Yan Li, Song Wei, Enlu Zhou, Tuo Zhao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1891-1899

CONTRA: Contrarian statistics for controlled variable selection

Mukund Sudarshan, Aahlad Puli, Lakshmi Subramanian, Sriram Sankararaman, Rajesh Ranganath; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1900-1908

Approximately Solving Mean Field Games via Entropy-Regularized Deep Reinforcement Learning

Kai Cui, Heinz Koeppl; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1909-1917

Moment-Based Variational Inference for Stochastic Differential Equations

Christian Wildner, Heinz Koeppl; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1918-1926

PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming

Alexander Lew, Monica Agrawal, David Sontag, Vikash Mansinghka; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1927-1935

Adaptive wavelet pooling for convolutional neural networks

Moritz Wolter, Jochen Garcke; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1936-1944

The Minecraft Kernel: Modelling correlated Gaussian Processes in the Fourier domain

Fergus Simpson, Alexis Boukouvalas, Vaclav Cadek, Elvijs Sarkans, Nicolas Durrande; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1945-1953

Exponential Convergence Rates of Classification Errors on Learning with SGD and Random Features

Shingo Yashima, Atsushi Nitanda, Taiji Suzuki; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1954-1962

High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding

Hannah Marienwald, Jean-Baptiste Fermanian, Gilles Blanchard; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1963-1971

Counterfactual Representation Learning with Balancing Weights

Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1972-1980

Gradient Descent in RKHS with Importance Labeling

Tomoya Murata, Taiji Suzuki; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1981-1989

Learning with Gradient Descent and Weakly Convex Losses

Dominic Richards, Mike Rabbat; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1990-1998

Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders

Andrew Bennett, Nathan Kallus, Lihong Li, Ali Mousavi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1999-2007

Approximate Data Deletion from Machine Learning Models

Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri, James Zou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2008-2016

Budgeted and Non-Budgeted Causal Bandits

Vineet Nair, Vishakha Patil, Gaurav Sinha; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2017-2025

Stability and Differential Privacy of Stochastic Gradient Descent for Pairwise Learning with Non-Smooth Loss

Zhenhuan Yang, Yunwen Lei, Siwei Lyu, Yiming Ying; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2026-2034

Equitable and Optimal Transport with Multiple Agents

Meyer Scetbon, Laurent Meunier, Jamal Atif, Marco Cuturi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2035-2043

A Variational Inference Approach to Learning Multivariate Wold Processes

Jalal Etesami, William Trouleau, Negar Kiyavash, Matthias Grossglauser, Patrick Thiran; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2044-2052

Active Online Learning with Hidden Shifting Domains

Yining Chen, Haipeng Luo, Tengyu Ma, Chicheng Zhang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2053-2061

No-Regret Algorithms for Private Gaussian Process Bandit Optimization

Abhimanyu Dubey; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2062-2070

The Teaching Dimension of Kernel Perceptron

Akash Kumar, Hanqi Zhang, Adish Singla, Yuxin Chen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2071-2079

Quantum Tensor Networks, Stochastic Processes, and Weighted Automata

Sandesh Adhikary, Siddarth Srinivasan, Jacob Miller, Guillaume Rabusseau, Byron Boots; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2080-2088

Localizing Changes in High-Dimensional Regression Models

Alessandro Rinaldo, Daren Wang, Qin Wen, Rebecca Willett, Yi Yu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2089-2097

On the Suboptimality of Negative Momentum for Minimax Optimization

Guodong Zhang, Yuanhao Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2098-2106

Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference

Maxime Vandegar, Michael Kagan, Antoine Wehenkel, Gilles Louppe; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2107-2115

Corralling Stochastic Bandit Algorithms

Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2116-2124

Context-Specific Likelihood Weighting

Nitesh Kumar, Ondřej Kuželka; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2125-2133

Learning Matching Representations for Individualized Organ Transplantation Allocation

Can Xu, Ahmed Alaa, Ioana Bica, Brent Ershoff, Maxime Cannesson, Mihaela van der Schaar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2134-2142

Stochastic Gradient Descent Meets Distribution Regression

Nicole Muecke; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2143-2151

Learning Contact Dynamics using Physically Structured Neural Networks

Andreas Hochlehnert, Alexander Terenin, Steindor Saemundsson, Marc Deisenroth; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2152-2160

Misspecification in Prediction Problems and Robustness via Improper Learning

Annie Marsden, John Duchi, Gregory Valiant; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2161-2169

Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization

Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2170-2178

Selective Classification via One-Sided Prediction

Aditya Gangrade, Anil Kag, Venkatesh Saligrama; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2179-2187

Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning

Hitesh Sapkota, Yiming Ying, Feng Chen, Qi Yu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2188-2196

vqSGD: Vector Quantized Stochastic Gradient Descent

Venkata Gandikota, Daniel Kane, Raj Kumar Maity, Arya Mazumdar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2197-2205

Smooth Bandit Optimization: Generalization to Holder Space

Yusha Liu, Yining Wang, Aarti Singh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2206-2214

List Learning with Attribute Noise

Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2215-2223

High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation

Kristjan Greenewald, Karthikeyan Shanmugam, Dmitriy Katz; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2224-2232

Fractional moment-preserving initialization schemes for training deep neural networks

Mert Gurbuzbalaban, Yuanhan Hu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2233-2241

Inductive Mutual Information Estimation: A Convex Maximum-Entropy Copula Approach

Yves-Laurent Kom Samo; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2242-2250

Federated f-Differential Privacy

Qinqing Zheng, Shuxiao Chen, Qi Long, Weijie Su; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2251-2259

Clustering multilayer graphs with missing nodes

Guillaume Braun, Hemant Tyagi, Christophe Biernacki; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2260-2268

Implicit Regularization via Neural Feature Alignment

Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2269-2277

Aggregating Incomplete and Noisy Rankings

Dimitris Fotakis, Alkis Kalavasis, Konstantinos Stavropoulos; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2278-2286

Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models

Sasi Kumar Murakonda, Reza Shokri, George Theodorakopoulos; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2287-2295

Optimal query complexity for private sequential learning against eavesdropping

Jiaming Xu, Kuang Xu, Dana Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2296-2304

Mirrorless Mirror Descent: A Natural Derivation of Mirror Descent

Suriya Gunasekar, Blake Woodworth, Nathan Srebro; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2305-2313

Differentiable Causal Discovery Under Unmeasured Confounding

Rohit Bhattacharya, Tushar Nagarajan, Daniel Malinsky, Ilya Shpitser; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2314-2322

The Sample Complexity of Meta Sparse Regression

Zhanyu Wang, Jean Honorio; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2323-2331

A Theory of Multiple-Source Adaptation with Limited Target Labeled Data

Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh, Ke Wu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2332-2340

Group testing for connected communities

Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas Diggavi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2341-2349

Federated Learning with Compression: Unified Analysis and Sharp Guarantees

Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari, Mehrdad Mahdavi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2350-2358

Variational Autoencoder with Learned Latent Structure

Marissa Connor, Gregory Canal, Christopher Rozell; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2359-2367

RankDistil: Knowledge Distillation for Ranking

Sashank Reddi, Rama Kumar Pasumarthi, Aditya Menon, Ankit Singh Rawat, Felix Yu, Seungyeon Kim, Andreas Veit, Sanjiv Kumar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2368-2376

Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data

Yu Gong, Hossein Hajimirsadeghi, Jiawei He, Thibaut Durand, Greg Mori; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2377-2385

On the Linear Convergence of Policy Gradient Methods for Finite MDPs

Jalaj Bhandari, Daniel Russo; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2386-2394

Minimal enumeration of all possible total effects in a Markov equivalence class

Richard Guo, Emilija Perkovic; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2395-2403

Differentially Private Weighted Sampling

Edith Cohen, Ofir Geri, Tamas Sarlos, Uri Stemmer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2404-2412

Learning the Truth From Only One Side of the Story

Heinrich Jiang, Qijia Jiang, Aldo Pacchiano; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2413-2421

Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples

Yixing Zhang, Xiuyuan Cheng, Galen Reeves; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2422-2430

Bayesian Inference with Certifiable Adversarial Robustness

Matthew Wicker, Luca Laurenti, Andrea Patane, Zhuotong Chen, Zheng Zhang, Marta Kwiatkowska; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2431-2439

Hierarchical Clustering in General Metric Spaces using Approximate Nearest Neighbors

Benjamin Moseley, Sergei Vassilvtiskii, Yuyan Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2440-2448

Statistical Guarantees for Transformation Based Models with applications to Implicit Variational Inference

Sean Plummer, Shuang Zhou, Anirban Bhattacharya, David Dunson, Debdeep Pati; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2449-2457

Reinforcement Learning for Mean Field Games with Strategic Complementarities

Kiyeob Lee, Desik Rengarajan, Dileep Kalathil, Srinivas Shakkottai; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2458-2466

Cluster Trellis: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering

Sebastian Macaluso, Craig Greenberg, Nicholas Monath, Ji Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2467-2475

Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?

Chaoqi Wang, Shengyang Sun, Roger Grosse; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2476-2484

On the Consistency of Metric and Non-Metric K-Medoids

He Jiang, Ery Arias-Castro; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2485-2493

Non-Stationary Off-Policy Optimization

Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2494-2502

Efficient Interpolation of Density Estimators

Paxton Turner, Jingbo Liu, Philippe Rigollet; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2503-2511

A Statistical Perspective on Coreset Density Estimation

Paxton Turner, Jingbo Liu, Philippe Rigollet; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2512-2520

Shuffled Model of Differential Privacy in Federated Learning

Antonious Girgis, Deepesh Data, Suhas Diggavi, Peter Kairouz, Ananda Theertha Suresh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2521-2529

CLAR: Contrastive Learning of Auditory Representations

Haider Al-Tahan, Yalda Mohsenzadeh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2530-2538

Designing Transportable Experiments Under S-admissability

My Phan, David Arbour, Drew Dimmery, Anup Rao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2539-2547

A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets

Gauthier Gidel, David Balduzzi, Wojciech Czarnecki, Marta Garnelo, Yoram Bachrach; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2548-2556

Private optimization without constraint violations

Andres Munoz, Umar Syed, Sergei Vassilvtiskii, Ellen Vitercik; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2557-2565

Direct Loss Minimization for Sparse Gaussian Processes

Yadi Wei, Rishit Sheth, Roni Khardon; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2566-2574

Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning

Zachary Charles, Jakub Konečný; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2575-2583

Linear Models are Robust Optimal Under Strategic Behavior

Wei Tang, Chien-Ju Ho, Yang Liu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2584-2592

Matérn Gaussian Processes on Graphs

Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Deisenroth, Nicolas Durrande; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2593-2601

Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs

Alden Green, Sivaraman Balakrishnan, Ryan Tibshirani; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2602-2610

Evaluating Model Robustness and Stability to Dataset Shift

Adarsh Subbaswamy, Roy Adams, Suchi Saria; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2611-2619

Continuum-Armed Bandits: A Function Space Perspective

Shashank Singh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2620-2628

Regret-Optimal Filtering

Oron Sabag, Babak Hassibi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2629-2637

Evading the Curse of Dimensionality in Unconstrained Private GLMs

Shuang Song, Thomas Steinke, Om Thakkar, Abhradeep Thakurta; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2638-2646

One-Sketch-for-All: Non-linear Random Features from Compressed Linear Measurements

Xiaoyun Li, Ping Li; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2647-2655

Reinforcement Learning for Constrained Markov Decision Processes

Ather Gattami, Qinbo Bai, Vaneet Aggarwal; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2656-2664

Principal Component Regression with Semirandom Observations via Matrix Completion

Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Maheshakya Wijewardena; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2665-2673

Ridge Regression with Over-parametrized Two-Layer Networks Converge to Ridgelet Spectrum

Sho Sonoda, Isao Ishikawa, Masahiro Ikeda; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2674-2682

Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration

Shengjia Zhao, Stefano Ermon; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2683-2691

Sample Elicitation

Jiaheng Wei, Zuyue Fu, Yang Liu, Xingyu Li, Zhuoran Yang, Zhaoran Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2692-2700

Random Coordinate Underdamped Langevin Monte Carlo

Zhiyan Ding, Qin Li, Jianfeng Lu, Stephen Wright; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2701-2709

Influence Decompositions For Neural Network Attribution

Kyle Reing, Greg Ver Steeg, Aram Galstyan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2710-2718

Variational inference for nonlinear ordinary differential equations

Sanmitra Ghosh, Paul Birrell, Daniela De Angelis; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2719-2727

Approximation Algorithms for Orthogonal Non-negative Matrix Factorization

Moses Charikar, Lunjia Hu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2728-2736

Fast Adaptation with Linearized Neural Networks

Wesley Maddox, Shuai Tang, Pablo Moreno, Andrew Gordon Wilson, Andreas Damianou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2737-2745

Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization

Jelena Diakonikolas, Constantinos Daskalakis, Michael I. Jordan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2746-2754

A Change of Variables Method For Rectangular Matrix-Vector Products

Edmond Cunningham, Madalina Fiterau; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2755-2763

Provably Efficient Actor-Critic for Risk-Sensitive and Robust Adversarial RL: A Linear-Quadratic Case

Yufeng Zhang, Zhuoran Yang, Zhaoran Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2764-2772

Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions

Hossein Taheri, Ramtin Pedarsani, Christos Thrampoulidis; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2773-2781

Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective

Jacky Zhang, Rajiv Khanna, Anastasios Kyrillidis, Sanmi Koyejo; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2782-2790

Causal Inference with Selectively Deconfounded Data

Kyra Gan, Andrew Li, Zachary Lipton, Sridhar Tayur; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2791-2799

Animal pose estimation from video data with a hierarchical von Mises-Fisher-Gaussian model

Libby Zhang, Tim Dunn, Jesse Marshall, Bence Olveczky, Scott Linderman; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2800-2808

Mirror Descent View for Neural Network Quantization

Thalaiyasingam Ajanthan, Kartik Gupta, Philip Torr, Richad Hartley, Puneet Dokania; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2809-2817

Power of Hints for Online Learning with Movement Costs

Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2818-2826

Stochastic Bandits with Linear Constraints

Aldo Pacchiano, Mohammad Ghavamzadeh, Peter Bartlett, Heinrich Jiang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2827-2835

Significance of Gradient Information in Bayesian Optimization

Shubhanshu Shekhar, Tara Javidi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2836-2844

Improving Adversarial Robustness via Unlabeled Out-of-Domain Data

Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2845-2853

DAG-Structured Clustering by Nearest Neighbors

Nicholas Monath, Manzil Zaheer, Kumar Avinava Dubey, Amr Ahmed, Andrew McCallum; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2854-2862

Hindsight Expectation Maximization for Goal-conditioned Reinforcement Learning

Yunhao Tang, Alp Kucukelbir; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2863-2871

Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience

Brian Brubach, Nathaniel Grammel, Will Ma, Aravind Srinivasan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2872-2880

Location Trace Privacy Under Conditional Priors

Casey Meehan, Kamalika Chaudhuri; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2881-2889

Large Scale K-Median Clustering for Stable Clustering Instances

Konstantin Voevodski; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2890-2898

An Optimal Reduction of TV-Denoising to Adaptive Online Learning

Dheeraj Baby, Xuandong Zhao, Yu-Xiang Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2899-2907

Differentially Private Monotone Submodular Maximization Under Matroid and Knapsack Constraints

Omid Sadeghi, Maryam Fazel; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2908-2916

Federated Multi-armed Bandits with Personalization

Chengshuai Shi, Cong Shen, Jing Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2917-2925

Hierarchical Inducing Point Gaussian Process for Inter-domian Observations

Luhuan Wu, Andrew Miller, Lauren Anderson, Geoff Pleiss, David Blei, John Cunningham; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2926-2934

Fast Statistical Leverage Score Approximation in Kernel Ridge Regression

Yifan Chen, Yun Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2935-2943

Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms

Tianyu Ding, Zhihui Zhu, Manolis Tsakiris, Rene Vidal, Daniel Robinson; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2944-2952

Accumulations of Projections—A Unified Framework for Random Sketches in Kernel Ridge Regression

Yifan Chen, Yun Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2953-2961

Robust hypothesis testing and distribution estimation in Hellinger distance

Ananda Theertha Suresh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2962-2970

Faster Kernel Interpolation for Gaussian Processes

Mohit Yadav, Daniel Sheldon, Cameron Musco; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2971-2979

SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups

Hyun-Suk Lee, Cong Shen, William Zame, Jang-Won Lee, Mihaela van der Schaar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2980-2988

Detection and Defense of Topological Adversarial Attacks on Graphs

Yingxue Zhang, Florence Regol, Soumyasundar Pal, Sakif Khan, Liheng Ma, Mark Coates; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2989-2997

Training a Single Bandit Arm

Eren Ozbay, Vijay Kamble; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2998-3006

Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation

Chen-Yu Wei, Mehdi Jafarnia Jahromi, Haipeng Luo, Rahul Jain; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3007-3015

Multi-Armed Bandits with Cost Subsidy

Deeksha Sinha, Karthik Abinav Sankararaman, Abbas Kazerouni, Vashist Avadhanula; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3016-3024

Causal Modeling with Stochastic Confounders

Thanh Vinh Vo, Pengfei Wei, Wicher Bergsma, Tze Yun Leong; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3025-3033

The Multiple Instance Learning Gaussian Process Probit Model

Fulton Wang, Ali Pinar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3034-3042

Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances

Hunter Lang, Aravind Reddy, David Sontag, Aravindan Vijayaraghavan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3043-3051

Meta Learning in the Continuous Time Limit

Ruitu Xu, Lin Chen, Amin Karbasi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3052-3060

Fast and Smooth Interpolation on Wasserstein Space

Sinho Chewi, Julien Clancy, Thibaut Le Gouic, Philippe Rigollet, George Stepaniants, Austin Stromme; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3061-3069

Efficient Balanced Treatment Assignments for Experimentation

David Arbour, Drew Dimmery, Anup Rao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3070-3078

Tensor Networks for Probabilistic Sequence Modeling

Jacob Miller, Guillaume Rabusseau, John Terilla; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3079-3087

Experimental Design for Regret Minimization in Linear Bandits

Andrew Wagenmaker, Julian Katz-Samuels, Kevin Jamieson; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3088-3096

DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural Networks

Shiyun Xu, Zhiqi Bu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3097-3105

Dynamic Cutset Networks

Chiradeep Roy, Tahrima Rahman, Hailiang Dong, Nicholas Ruozzi, Vibhav Gogate; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3106-3114

Associative Convolutional Layers

Hamed Omidvar, Vahideh Akhlaghi, Hao Su, Massimo Franceschetti, Rajesh Gupta; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3115-3123

Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon

Jeremiah Liu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3124-3132

Kernel Interpolation for Scalable Online Gaussian Processes

Samuel Stanton, Wesley Maddox, Ian Delbridge, Andrew Gordon Wilson; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3133-3141

Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks

Huichen Li, Linyi Li, Xiaojun Xu, Xiaolu Zhang, Shuang Yang, Bo Li; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3142-3150

Contrastive learning of strong-mixing continuous-time stochastic processes

Bingbin Liu, Pradeep Ravikumar, Andrej Risteski; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3151-3159

TenIPS: Inverse Propensity Sampling for Tensor Completion

Chengrun Yang, Lijun Ding, Ziyang Wu, Madeleine Udell; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3160-3168

Sketch based Memory for Neural Networks

Rina Panigrahy, Xin Wang, Manzil Zaheer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3169-3177

Uniform Consistency of Cross-Validation Estimators for High-Dimensional Ridge Regression

Pratik Patil, Yuting Wei, Alessandro Rinaldo, Ryan Tibshirani; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3178-3186

A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks

Zhiqi Bu, Shiyun Xu, Kan Chen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3187-3195

Semi-Supervised Aggregation of Dependent Weak Supervision Sources With Performance Guarantees

Alessio Mazzetto, Dylan Sam, Andrew Park, Eli Upfal, Stephen Bach; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3196-3204

Principal Subspace Estimation Under Information Diffusion

Fan Zhou, Ping Li, Zhixin Zhou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3205-3213

A Hybrid Approximation to the Marginal Likelihood

Eric Chuu, Debdeep Pati, Anirban Bhattacharya; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3214-3222

Prediction with Finitely many Errors Almost Surely

Changlong Wu, Narayana Santhanam; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3223-3231

Density of States Estimation for Out of Distribution Detection

Warren Morningstar, Cusuh Ham, Andrew Gallagher, Balaji Lakshminarayanan, Alex Alemi, Joshua Dillon; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3232-3240

Product Manifold Learning

Sharon Zhang, Amit Moscovich, Amit Singer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3241-3249

Automatic Differentiation Variational Inference with Mixtures

Warren Morningstar, Sharad Vikram, Cusuh Ham, Andrew Gallagher, Joshua Dillon; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3250-3258

Fair for All: Best-effort Fairness Guarantees for Classification

Anilesh Krishnaswamy, Zhihao Jiang, Kangning Wang, Yu Cheng, Kamesh Munagala; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3259-3267

Taming heavy-tailed features by shrinkage

Ziwei Zhu, Wenjing Zhou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3268-3276

Efficient Designs Of SLOPE Penalty Sequences In Finite Dimension

Yiliang Zhang, Zhiqi Bu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3277-3285

Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation

Mayee Chen, Benjamin Cohen-Wang, Stephen Mussmann, Frederic Sala, Christopher Re; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3286-3294

Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent

Frederik Kunstner, Raunak Kumar, Mark Schmidt; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3295-3303

Provably Efficient Safe Exploration via Primal-Dual Policy Optimization

Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo Jovanovic; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3304-3312

Understanding Robustness in Teacher-Student Setting: A New Perspective

Zhuolin Yang, Zhaoxi Chen, Tiffany Cai, Xinyun Chen, Bo Li, Yuandong Tian; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3313-3321

Non-asymptotic Performance Guarantees for Neural Estimation of f-Divergences

Sreejith Sreekumar, Zhengxin Zhang, Ziv Goldfeld; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3322-3330

Finite-Sample Regret Bound for Distributionally Robust Offline Tabular Reinforcement Learning

Zhengqing Zhou, Zhengyuan Zhou, Qinxun Bai, Linhai Qiu, Jose Blanchet, Peter Glynn; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3331-3339

Online Model Selection for Reinforcement Learning with Function Approximation

Jonathan Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3340-3348

Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC

Priyank Jaini, Didrik Nielsen, Max Welling; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3349-3357

Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT

Antti Koskela, Joonas Jälkö, Lukas Prediger, Antti Honkela; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3358-3366

A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits

Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3367-3375

Good Classifiers are Abundant in the Interpolating Regime

Ryan Theisen, Jason Klusowski, Michael Mahoney; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3376-3384

No-Regret Reinforcement Learning with Heavy-Tailed Rewards

Vincent Zhuang, Yanan Sui; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3385-3393

A Spectral Analysis of Dot-product Kernels

Meyer Scetbon, Zaid Harchaoui; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3394-3402

Towards Flexible Device Participation in Federated Learning

Yichen Ruan, Xiaoxi Zhang, Shu-Che Liang, Carlee Joe-Wong; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3403-3411

Active Learning under Label Shift

Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3412-3420

Tracking Regret Bounds for Online Submodular Optimization

Tatsuya Matsuoka, Shinji Ito, Naoto Ohsaka; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3421-3429

Offline detection of change-points in the mean for stationary graph signals.

Alejandro de la Concha Duarte, Nicolas Vayatis, Argyris Kalogeratos; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3430-3438

Hyperbolic graph embedding with enhanced semi-implicit variational inference.

Ali Lotfi Rezaabad, Rahi Kalantari, Sriram Vishwanath, Mingyuan Zhou, Jonathan Tamir; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3439-3447

Rao-Blackwellised parallel MCMC

Tobias Schwedes, Ben Calderhead; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3448-3456

Improving KernelSHAP: Practical Shapley Value Estimation Using Linear Regression

Ian Covert, Su-In Lee; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3457-3465

Calibrated Adaptive Probabilistic ODE Solvers

Nathanael Bosch, Philipp Hennig, Filip Tronarp; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3466-3474

Online Robust Control of Nonlinear Systems with Large Uncertainty

Dimitar Ho, Hoang Le, John Doyle, Yisong Yue; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3475-3483

Probabilistic Sequential Matrix Factorization

Omer Deniz Akyildiz, Gerrit van den Burg, Theodoros Damoulas, Mark Steel; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3484-3492

An Analysis of LIME for Text Data

Dina Mardaoui, Damien Garreau; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3493-3501

Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side-Information

Prathamesh Mayekar, Ananda Theertha Suresh, Himanshu Tyagi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3502-3510

Scalable Gaussian Process Variational Autoencoders

Metod Jazbec, Matt Ashman, Vincent Fortuin, Michael Pearce, Stephan Mandt, Gunnar Rätsch; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3511-3519

Causal Autoregressive Flows

Ilyes Khemakhem, Ricardo Monti, Robert Leech, Aapo Hyvarinen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3520-3528

Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models

Jan Achterhold, Joerg Stueckler; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3529-3537

A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces

Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta, Emilie Kaufmann, Michal Valko; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3538-3546

Spectral Tensor Train Parameterization of Deep Learning Layers

Anton Obukhov, Maxim Rakhuba, Alexander Liniger, Zhiwu Huang, Stamatios Georgoulis, Dengxin Dai, Luc Van Gool; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3547-3555

Local SGD: Unified Theory and New Efficient Methods

Eduard Gorbunov, Filip Hanzely, Peter Richtarik; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3556-3564

Towards a Theoretical Understanding of the Robustness of Variational Autoencoders

Alexander Camuto, Matthew Willetts, Stephen Roberts, Chris Holmes, Tom Rainforth; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3565-3573

Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization

Vikas Garg, Adam Tauman Kalai, Katrina Ligett, Steven Wu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3574-3582

The Base Measure Problem and its Solution

Alexey Radul, Boris Alexeev; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3583-3591

Revisiting Projection-free Online Learning: the Strongly Convex Case

Ben Kretzu, Dan Garber; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3592-3600

A Theoretical Characterization of Semi-supervised Learning with Self-training for Gaussian Mixture Models

Samet Oymak, Talha Cihad Gulcu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3601-3609

Logistic Q-Learning

Joan Bas-Serrano, Sebastian Curi, Andreas Krause, Gergely Neu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3610-3618

Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model

Nafiseh Ghoroghchian, Gautam Dasarathy, Stark Draper; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3619-3627

Sequential Random Sampling Revisited: Hidden Shuffle Method

Michael Shekelyan, Graham Cormode; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3628-3636

Dirichlet Pruning for Convolutional Neural Networks

Kamil Adamczewski, Mijung Park; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3637-3645

Couplings for Multinomial Hamiltonian Monte Carlo

Kai Xu, Tor Erlend Fjelde, Charles Sutton, Hong Ge; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3646-3654

Learning Bijective Feature Maps for Linear ICA

Alexander Camuto, Matthew Willetts, Chris Holmes, Brooks Paige, Stephen Roberts; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3655-3663

Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain

Takahiro Mimori, Keiko Sasada, Hirotaka Matsui, Issei Sato; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3664-3672

One-pass Stochastic Gradient Descent in overparametrized two-layer neural networks

Hanjing Zhu, Jiaming Xu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3673-3681

On the Memory Mechanism of Tensor-Power Recurrent Models

Hejia Qiu, Chao Li, Ying Weng, Zhun Sun, Xingyu He, Qibin Zhao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3682-3690

Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits

Marc Abeille, Louis Faury, Clement Calauzenes; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3691-3699

Causal Inference under Networked Interference and Intervention Policy Enhancement

Yunpu Ma, Volker Tresp; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3700-3708

GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences

Mucong Ding, Constantinos Daskalakis, Soheil Feizi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3709-3717

Latent Gaussian process with composite likelihoods and numerical quadrature

Siddharth Ramchandran, Miika Koskinen, Harri Lähdesmäki; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3718-3726

Deep Generative Missingness Pattern-Set Mixture Models

Sahra Ghalebikesabi, Rob Cornish, Chris Holmes, Luke Kelly; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3727-3735

Minimax Estimation of Laplacian Constrained Precision Matrices

Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel Palomar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3736-3744

A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models

Jiaxin Zhang, Sirui Bi, Guannan Zhang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3745-3753

Distribution Regression for Sequential Data

Maud Lemercier, Cristopher Salvi, Theodoros Damoulas, Edwin Bonilla, Terry Lyons; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3754-3762

Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions

Yihan Wu, Aleksandar Bojchevski, Aleksei Kuvshinov, Stephan Günnemann; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3763-3771

Direct-Search for a Class of Stochastic Min-Max Problems

Sotirios-Konstantinos Anagnostidis, Aurelien Lucchi, Youssef Diouane; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3772-3780

Self-Supervised Steering Angle Prediction for Vehicle Control Using Visual Odometry

Qadeer Khan, Patrick Wenzel, Daniel Cremers; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3781-3789

Learning Temporal Point Processes with Intermittent Observations

Vinayak Gupta, Srikanta Bedathur, Sourangshu Bhattacharya, Abir De; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3790-3798

On the number of linear functions composing deep neural network: Towards a refined definition of neural networks complexity

Yuuki Takai, Akiyoshi Sannai, Matthieu Cordonnier; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3799-3807

Robust Learning under Strong Noise via SQs

Ioannis Anagnostides, Themis Gouleakis, Ali Marashian; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3808-3816

Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models

Leena C. Vankadara, Sebastian Bordt, Ulrike von Luxburg, Debarghya Ghoshdastidar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3817-3825

Convergence Properties of Stochastic Hypergradients

Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3826-3834

Entropy Partial Transport with Tree Metrics: Theory and Practice

Tam Le, Truyen Nguyen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3835-3843

Combinatorial Gaussian Process Bandits with Probabilistically Triggered Arms

Ilker Demirel, Cem Tekin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3844-3852

Differentiable Divergences Between Time Series

Mathieu Blondel, Arthur Mensch, Jean-Philippe Vert; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3853-3861

Local Competition and Stochasticity for Adversarial Robustness in Deep Learning

Konstantinos Panousis, Sotirios Chatzis, Antonios Alexos, Sergios Theodoridis; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3862-3870

Differentiating the Value Function by using Convex Duality

Sheheryar Mehmood, Peter Ochs; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3871-3879

Rate-Regularization and Generalization in Variational Autoencoders

Alican Bozkurt, Babak Esmaeili, Jean-Baptiste Tristan, Dana Brooks, Jennifer Dy, Jan-Willem van de Meent; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3880-3888

Asymptotics of Ridge(less) Regression under General Source Condition

Dominic Richards, Jaouad Mourtada, Lorenzo Rosasco; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3889-3897

Longitudinal Variational Autoencoder

Siddharth Ramchandran, Gleb Tikhonov, Kalle Kujanpää, Miika Koskinen, Harri Lähdesmäki; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3898-3906

An Adaptive-MCMC Scheme for Setting Trajectory Lengths in Hamiltonian Monte Carlo

Matthew Hoffman, Alexey Radul, Pavel Sountsov; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3907-3915

Model updating after interventions paradoxically introduces bias

James Liley, Samuel Emerson, Bilal Mateen, Catalina Vallejos, Louis Aslett, Sebastian Vollmer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3916-3924

On Multilevel Monte Carlo Unbiased Gradient Estimation for Deep Latent Variable Models

Yuyang Shi, Rob Cornish; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3925-3933

Flow-based Alignment Approaches for Probability Measures in Different Spaces

Tam Le, Nhat Ho, Makoto Yamada; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3934-3942

LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads

Hossein Shokri Ghadikolaei, Sebastian Stich, Martin Jaggi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3943-3951

Learning Shared Subgraphs in Ising Model Pairs

Burak Varici, Saurabh Sihag, Ali Tajer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3952-3960

Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling

Setareh Ariafar, Zelda Mariet, Dana Brooks, Jennifer Dy, Jasper Snoek; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3961-3969

Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty

Guang Zhao, Edward Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3970-3978

Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex Optimization

Peiyuan Zhang, Antonio Orvieto, Hadi Daneshmand, Thomas Hofmann, Roy S. Smith; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3979-3987

Improved Exploration in Factored Average-Reward MDPs

Mohammad Sadegh Talebi, Anders Jonsson, Odalric Maillard; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3988-3996

Toward a General Theory of Online Selective Sampling: Trading Off Mistakes and Queries

Steve Hanneke, Liu Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3997-4005

Regularized ERM on random subspaces

Andrea Della Vecchia, Jaouad Mourtada, Ernesto De Vito, Lorenzo Rosasco; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4006-4014

On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning

Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4015-4023

Meta-Learning Divergences for Variational Inference

Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4024-4032

Hidden Cost of Randomized Smoothing

Jeet Mohapatra, Ching-Yun Ko, Lily Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4033-4041

Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates

Sebastian Stich, Amirkeivan Mohtashami, Martin Jaggi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4042-4050

Improving Classifier Confidence using Lossy Label-Invariant Transformations

Sooyong Jang, Insup Lee, James Weimer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4051-4059

Graph Gamma Process Linear Dynamical Systems

Rahi Kalantari, Mingyuan Zhou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4060-4068

Does Invariant Risk Minimization Capture Invariance?

Pritish Kamath, Akilesh Tangella, Danica Sutherland, Nathan Srebro; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4069-4077

A unified view of likelihood ratio and reparameterization gradients

Paavo Parmas, Masashi Sugiyama; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4078-4086

A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!

Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtarik, Sebastian Stich; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4087-4095

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