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Volume 206: International Conference on Artificial Intelligence and Statistics, 25-27 April 2023, Palau de Congressos, Valencia, Spain

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Editors: Francisco Ruiz, Jennifer Dy, Jan-Willem van de Meent

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Contents:

Notable Papers

Blessing of Class Diversity in Pre-training

Yulai Zhao, Jianshu Chen, Simon Du; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:283-305

BaCaDI: Bayesian Causal Discovery with Unknown Interventions

Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1411-1436

Discovering Many Diverse Solutions with Bayesian Optimization

Natalie Maus, Kaiwen Wu, David Eriksson, Jacob Gardner; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1779-1798

Multilevel Bayesian Quadrature

Kaiyu Li, Daniel Giles, Toni Karvonen, Serge Guillas, Francois-Xavier Briol; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1845-1868

Distance-to-Set Priors and Constrained Bayesian Inference

Rick Presman, Jason Xu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2310-2326

Error Estimation for Random Fourier Features

Junwen Yao, N. Benjamin Erichson, Miles E. Lopes; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2348-2364

Noisy Low-rank Matrix Optimization: Geometry of Local Minima and Convergence Rate

Ziye Ma, Somayeh Sojoudi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3125-3150

Generalized PTR: User-Friendly Recipes for Data-Adaptive Algorithms with Differential Privacy

Rachel Redberg, Yuqing Zhu, Yu-Xiang Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3977-4005

A Tale of Sampling and Estimation in Discounted Reinforcement Learning

Alberto Maria Metelli, Mirco Mutti, Marcello Restelli; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4575-4601

An Efficient and Continuous Voronoi Density Estimator

Giovanni Luca Marchetti, Vladislav Polianskii, Anastasiia Varava, Florian T. Pokorny, Danica Kragic; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4732-4744

Safe Sequential Testing and Effect Estimation in Stratified Count Data

Rosanne Turner, Peter Grunwald; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4880-4893

Particle algorithms for maximum likelihood training of latent variable models

Juan Kuntz, Jen Ning Lim, Adam M. Johansen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5134-5180

Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation

Henry B. Moss, Sebastian W. Ober, Victor Picheny; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5213-5230

Implications of sparsity and high triangle density for graph representation learning

Hannah Sansford, Alexander Modell, Nick Whiteley, Patrick Rubin-Delanchy; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5449-5473

The Schrödinger Bridge between Gaussian Measures has a Closed Form

Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5802-5833

Federated Learning under Distributed Concept Drift

Ellango Jothimurugesan, Kevin Hsieh, Jianyu Wang, Gauri Joshi, Phillip B. Gibbons; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5834-5853

Data Banzhaf: A Robust Data Valuation Framework for Machine Learning

Jiachen T. Wang, Ruoxi Jia; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6388-6421

Indeterminacy in Generative Models: Characterization and Strong Identifiability

Quanhan Xi, Benjamin Bloem-Reddy; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6912-6939

Do Bayesian Neural Networks Need To Be Fully Stochastic?

Mrinank Sharma, Sebastian Farquhar, Eric Nalisnick, Tom Rainforth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7694-7722

Mode-Seeking Divergences: Theory and Applications to GANs

Cheuk Ting Li, Farzan Farnia; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8321-8350

Fix-A-Step: Semi-supervised Learning From Uncurated Unlabeled Data

Zhe Huang, Mary-Joy Sidhom, Benjamin Wessler, Michael C. Hughes; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8373-8394

Rethinking Initialization of the Sinkhorn Algorithm

James Thornton, Marco Cuturi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8682-8698

Don’t be fooled: label leakage in explanation methods and the importance of their quantitative evaluation

Neil Jethani, Adriel Saporta, Rajesh Ranganath; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8925-8953

Origins of Low-Dimensional Adversarial Perturbations

Elvis Dohmatob, Chuan Guo, Morgane Goibert; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9221-9237

Scalable Bicriteria Algorithms for Non-Monotone Submodular Cover

Victoria Crawford; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9517-9537

Huber-robust confidence sequences

Hongjian Wang, Aaditya Ramdas; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9662-9679

Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation

Garud Iyengar, Henry Lam, Tianyu Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9976-10011

Who Should Predict? Exact Algorithms For Learning to Defer to Humans

Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David Sontag; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10520-10545

Implicit Graphon Neural Representation

Xinyue Xia, Gal Mishne, Yusu Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10619-10634

Fitting low-rank models on egocentrically sampled partial networks

Ga Ming Angus Chan, Tianxi Li; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10635-10649

The Power of Recursion in Graph Neural Networks for Counting Substructures

Behrooz Tahmasebi, Derek Lim, Stefanie Jegelka; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11023-11042

Using Sliced Mutual Information to Study Memorization and Generalization in Deep Neural Networks

Shelvia Wongso, Rohan Ghosh, Mehul Motani; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11608-11629

Regular Papers

Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation

Shinsaku Sakaue, Taihei Oki; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1-10

Meta-Uncertainty in Bayesian Model Comparison

Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11-29

PAC Learning of Halfspaces with Malicious Noise in Nearly Linear Time

Jie Shen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:30-46

Entropic Risk Optimization in Discounted MDPs

Jia Lin Hau, Marek Petrik, Mohammad Ghavamzadeh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:47-76

Acceleration of Frank-Wolfe Algorithms with Open-Loop Step-Sizes

Elias Wirth, Thomas Kerdreux, Sebastian Pokutta; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:77-100

An Online and Unified Algorithm for Projection Matrix Vector Multiplication with Application to Empirical Risk Minimization

Lianke Qin, Zhao Song, Lichen Zhang, Danyang Zhuo; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:101-156

Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision

Jieyu Zhang, Linxin Song, Alex Ratner; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:157-171

Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods

Aleksandr Beznosikov, Eduard Gorbunov, Hugo Berard, Nicolas Loizou; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:172-235

Scalable marked point processes for exchangeable and non-exchangeable event sequences

Aristeidis Panos, Ioannis Kosmidis, Petros Dellaportas; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:236-252

Bayesian Variable Selection in a Million Dimensions

Martin Jankowiak; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:253-282

Barlow Graph Auto-Encoder for Unsupervised Network Embedding

Rayyan Ahmad Khan, Martin Kleinsteuber; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:306-322

Gradient-Informed Neural Network Statistical Robustness Estimation

Karim TIT, Teddy Furon, Mathias Rousset; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:323-334

Online Defense Strategies for Reinforcement Learning Against Adaptive Reward Poisoning

Andi Nika, Adish Singla, Goran Radanovic; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:335-358

A Case of Exponential Convergence Rates for SVM

Vivien Cabannnes, Stefano Vigogna; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:359-374

Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning

Ruitu Xu, Yifei Min, Tianhao Wang, Michael I. Jordan, Zhaoran Wang, Zhuoran Yang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:375-407

Adaptive Cholesky Gaussian Processes

Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Munoz, Wouter Boomsma, Jes Frellsen, Soren Hauberg; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:408-452

Sample Complexity of Kernel-Based Q-Learning

Sing-Yuan Yeh, Fu-Chieh Chang, Chang-Wei Yueh, Pei-Yuan Wu, Alberto Bernacchia, Sattar Vakili; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:453-469

A principled framework for the design and analysis of token algorithms

Hadrien Hendrikx; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:470-489

Learning k-qubit Quantum Operators via Pauli Decomposition

Mohsen Heidari, Wojciech Szpankowski; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:490-504

Semi-Verified PAC Learning from the Crowd

Shiwei Zeng, Jie Shen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:505-522

On the Capacity Limits of Privileged ERM

Michal Sharoni, Sivan Sabato; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:523-534

USIM Gate: UpSampling Module for Segmenting Precise Boundaries concerning Entropy

Kyungsu Lee, Haeyun Lee, Jae Youn Hwang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:535-562

Bayesian Structure Scores for Probabilistic Circuits

Yang Yang, Gennaro Gala, Robert Peharz; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:563-575

Langevin Diffusion Variational Inference

Tomas Geffner, Justin Domke; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:576-593

Overcoming Prior Misspecification in Online Learning to Rank

Javad Azizi, Ofer Meshi, Masrour Zoghi, Maryam Karimzadehgan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:594-614

Catalyst Acceleration of Error Compensated Methods Leads to Better Communication Complexity

Xun Qian, Hanze Dong, Tong Zhang, Peter Richtarik; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:615-649

Kernel Conditional Moment Constraints for Confounding Robust Inference

Kei Ishikawa, Niao He; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:650-674

Meta-learning for Robust Anomaly Detection

Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Yasuhiro Fujiwara; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:675-691

Learning in RKHM: a C*-Algebraic Twist for Kernel Machines

Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:692-708

From Shapley Values to Generalized Additive Models and back

Sebastian Bordt, Ulrike von Luxburg; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:709-745

Estimating Conditional Average Treatment Effects with Missing Treatment Information

Milan Kuzmanovic, Tobias Hatt, Stefan Feuerriegel; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:746-766

Global Convergence of Over-parameterized Deep Equilibrium Models

Zenan Ling, Xingyu Xie, Qiuhao Wang, Zongpeng Zhang, Zhouchen Lin; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:767-787

A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action Space

Zhaozhuo Xu, Zhao Song, Anshumali Shrivastava; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:788-836

Adversarial De-confounding in Individualised Treatment Effects Estimation

Vinod K. Chauhan, Soheila Molaei, Marzia Hoque Tania, Anshul Thakur, Tingting Zhu, David A. Clifton; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:837-849

Fast Distributed k-Means with a Small Number of Rounds

Tom Hess, Ron Visbord, Sivan Sabato; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:850-874

A New Causal Decomposition Paradigm towards Health Equity

Xinwei Sun, Xiangyu Zheng, Jim Weinstein; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:875-890

Matching Map Recovery with an Unknown Number of Outliers

Arshak Minasyan, Tigran Galstyan, Sona Hunanyan, Arnak Dalalyan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:891-906

Characterizing Internal Evasion Attacks in Federated Learning

Taejin Kim, Shubhranshu Singh, Nikhil Madaan, Carlee Joe-Wong; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:907-921

Optimal and Private Learning from Human Response Data

Duc Nguyen, Anderson Ye Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:922-958

Bayesian Optimization with Conformal Prediction Sets

Samuel Stanton, Wesley Maddox, Andrew Gordon Wilson; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:959-986

Alternating Projected SGD for Equality-constrained Bilevel Optimization

Quan Xiao, Han Shen, Wotao Yin, Tianyi Chen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:987-1023

Improved Robust Algorithms for Learning with Discriminative Feature Feedback

Sivan Sabato; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1024-1036

Weisfeiler and Leman go Hyperbolic: Learning Distance Preserving Node Representations

Giannis Nikolentzos, Michail Chatzianastasis, Michalis Vazirgiannis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1037-1054

Can 5th Generation Local Training Methods Support Client Sampling? Yes!

Michał Grudzień, Grigory Malinovsky, Peter Richtarik; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1055-1092

qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization

Raul Astudillo, Zhiyuan Jerry Lin, Eytan Bakshy, Peter Frazier; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1093-1114

Bayesian Hierarchical Models for Counterfactual Estimation

Natraj Raman, Daniele Magazzeni, Sameena Shah; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1115-1128

Sequential Gradient Descent and Quasi-Newton’s Method for Change-Point Analysis

Xianyang Zhang, Trisha Dawn; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1129-1143

Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework

Runzhe Wan, Lin Ge, Rui Song; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1144-1173

Compress Then Test: Powerful Kernel Testing in Near-linear Time

Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1174-1218

Select and Optimize: Learning to solve large-scale TSP instances

Hanni Cheng, Haosi Zheng, Ya Cong, Weihao Jiang, Shiliang Pu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1219-1231

Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity

Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1232-1300

Testing of Horn Samplers

Ansuman Banerjee, Shayak Chakraborty, Sourav Chakraborty, Kuldeep S. Meel, Uddalok Sarkar, Sayantan Sen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1301-1330

Coordinate Ascent for Off-Policy RL with Global Convergence Guarantees

Hsin-En Su, Yen-Ju Chen, Ping-Chun Hsieh, Xi Liu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1331-1378

Positional Encoder Graph Neural Networks for Geographic Data

Konstantin Klemmer, Nathan S. Safir, Daniel B. Neill; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1379-1389

Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces

Omer Gottesman, Kavosh Asadi, Cameron S. Allen, Samuel Lobel, George Konidaris, Michael Littman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1390-1410

Statistical Analysis of Karcher Means for Random Restricted PSD Matrices

Hengchao Chen, Xiang Li, Qiang Sun; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1437-1456

Differentially Private Synthetic Control

Saeyoung Rho, Rachel Cummings, Vishal Misra; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1457-1491

Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes

Felix Jimenez, Matthias Katzfuss; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1492-1512

On the Neural Tangent Kernel Analysis of Randomly Pruned Neural Networks

Hongru Yang, Zhangyang Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1513-1553

Riemannian Accelerated Gradient Methods via Extrapolation

Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1554-1585

Flexible risk design using bi-directional dispersion

Matthew J. Holland; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1586-1623

Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles

Jung-Hun Kim, Se-Young Yun, Minchan Jeong, Junhyun Nam, Jinwoo Shin, Richard Combes; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1624-1645

Deep equilibrium models as estimators for continuous latent variables

Russell Tsuchida, Cheng Soon Ong; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1646-1671

Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data

Batiste Le Bars, Aurélien Bellet, Marc Tommasi, Erick Lavoie, Anne-Marie Kermarrec; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1672-1702

A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces

Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1703-1718

A Constant-Factor Approximation Algorithm for Reconciliation $k$-Median

Joachim Spoerhase, Kamyar Khodamoradi, Benedikt Riegel, Bruno Ordozgoiti, Aristides Gionis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1719-1746

Neural Laplace Control for Continuous-time Delayed Systems

Samuel Holt, Alihan Hüyük, Zhaozhi Qian, Hao Sun, Mihaela van der Schaar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1747-1778

BlitzMask: Real-Time Instance Segmentation Approach for Mobile Devices

Vitalii Bulygin, Dmytro Mykheievskyi, Kyrylo Kuchynskyi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1799-1811

Exact Gradient Computation for Spiking Neural Networks via Forward Propagation

Jane H. Lee, Saeid Haghighatshoar, Amin Karbasi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1812-1831

Uni6Dv2: Noise Elimination for 6D Pose Estimation

Mingshan Sun, Ye Zheng, Tianpeng Bao, Jianqiu Chen, Guoqiang Jin, Liwei Wu, Rui Zhao, Xiaoke Jiang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1832-1844

Direct Inference of Effect of Treatment (DIET) for a Cookieless World

Shiv Shankar, Ritwik Sinha, Saayan Mitra, Moumita Sinha, Madalina Fiterau; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1869-1887

The Ordered Matrix Dirichlet for State-Space Models

Niklas Stoehr, Benjamin J. Radford, Ryan Cotterell, Aaron Schein; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1888-1903

Energy-Based Models for Functional Data using Path Measure Tilting

Jen Ning Lim, Sebastian Vollmer, Lorenz Wolf, Andrew Duncan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1904-1923

Frequentist Uncertainty Quantification in Semi-Structured Neural Networks

Emilio Dorigatti, Benjamin Schubert, Bernd Bischl, David Ruegamer; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1924-1941

NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge

Xiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1942-1964

One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning

Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1965-2001

Variational Inference for Neyman-Scott Processes

Chengkuan Hong, Christian Shelton; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2002-2018

Graph Alignment Kernels using Weisfeiler and Leman Hierarchies

Giannis Nikolentzos, Michalis Vazirgiannis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2019-2034

Geometric Random Walk Graph Neural Networks via Implicit Layers

Giannis Nikolentzos, Michalis Vazirgiannis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2035-2053

Model-X Sequential Testing for Conditional Independence via Testing by Betting

Shalev Shaer, Gal Maman, Yaniv Romano; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2054-2086

Mixed-Effect Thompson Sampling

Imad Aouali, Branislav Kveton, Sumeet Katariya; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2087-2115

Mixed Linear Regression via Approximate Message Passing

Nelvin Tan, Ramji Venkataramanan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2116-2131

EEGNN: Edge Enhanced Graph Neural Network with a Bayesian Nonparametric Graph Model

Yirui Liu, Xinghao Qiao, Liying Wang, Jessica Lam; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2132-2146

Estimating Total Correlation with Mutual Information Estimators

Ke Bai, Pengyu Cheng, Weituo Hao, Ricardo Henao, Larry Carin; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2147-2164

Vector Optimization with Stochastic Bandit Feedback

Cagin Ararat, Cem Tekin; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2165-2190

Knowledge Acquisition for Human-In-The-Loop Image Captioning

Ervine Zheng, Qi Yu, Rui Li, Pengcheng Shi, Anne Haake; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2191-2206

A Statistical Analysis of Polyak-Ruppert Averaged Q-Learning

Xiang Li, Wenhao Yang, Jiadong Liang, Zhihua Zhang, Michael I. Jordan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2207-2261

Linear Convergence of Gradient Descent For Finite Width Over-parametrized Linear Networks With General Initialization

Ziqing Xu, Hancheng Min, Salma Tarmoun, Enrique Mallada, Rene Vidal; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2262-2284

“Plus/minus the learning rate”: Easy and Scalable Statistical Inference with SGD

Jerry Chee, Hwanwoo Kim, Panos Toulis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2285-2309

Fast Computation of Branching Process Transition Probabilities via ADMM

Achal Awasthi, Jason Xu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2327-2347

AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization

Feihu Huang, Xidong Wu, Zhengmian Hu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2365-2389

Classification of Adolescents’ Risky Behavior in Instant Messaging Conversations

Jaromı́r Plhák, Ondřej Sotolář, Michaela Lebedı́ková, David Šmahel; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2390-2404

Robust Linear Regression for General Feature Distribution

Tom Norman, Nir Weinberger, Kfir Y. Levy; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2405-2435

Fair learning with Wasserstein barycenters for non-decomposable performance measures

Solenne Gaucher, Nicolas Schreuder, Evgenii Chzhen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2436-2459

Deep Neural Networks with Efficient Guaranteed Invariances

Matthias Rath, Alexandru Paul Condurache; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2460-2480

Fast Block Coordinate Descent for Non-Convex Group Regularizations

Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2481-2493

AUC-based Selective Classification

Andrea Pugnana, Salvatore Ruggieri; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2494-2514

Nonparametric Indirect Active Learning

Shashank Singh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2515-2541

Resolving the Approximability of Offline and Online Non-monotone DR-Submodular Maximization over General Convex Sets

Loay Mualem, Moran Feldman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2542-2564

{PF}$^2$ES: Parallel Feasible Pareto Frontier Entropy Search for Multi-Objective Bayesian Optimization

Jixiang Qing, Henry B. Moss, Tom Dhaene, Ivo Couckuyt; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2565-2588

Learning Constrained Structured Spaces with Application to Multi-Graph Matching

Hedda Cohen Indelman, Tamir Hazan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2589-2602

On the Strategyproofness of the Geometric Median

El-Mahdi El-Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui, Lê-Nguyên Hoang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2603-2640

Covariate-informed Representation Learning to Prevent Posterior Collapse of iVAE

Young-Geun Kim, Ying Liu, Xue-Xin Wei; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2641-2660

EGG-GAE: scalable graph neural networks for tabular data imputation

Lev Telyatnikov, Simone Scardapane; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2661-2676

Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables

Mengdi Xu, Peide Huang, Yaru Niu, Visak Kumar, Jielin Qiu, Chao Fang, Kuan-Hui Lee, Xuewei Qi, Henry Lam, Bo Li, Ding Zhao; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2677-2703

Weather2K: A Multivariate Spatio-Temporal Benchmark Dataset for Meteorological Forecasting Based on Real-Time Observation Data from Ground Weather Stations

Xun Zhu, Yutong Xiong, Ming Wu, Gaozhen Nie, Bin Zhang, Ziheng Yang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2704-2722

Improved Rate of First Order Algorithms for Entropic Optimal Transport

Yiling Luo, Yiling Xie, Xiaoming Huo; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2723-2750

Conformal Off-Policy Prediction

Yingying Zhang, Chengchun Shi, Shikai Luo; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2751-2768

Sparse Spectral Bayesian Permanental Process with Generalized Kernel

Jeremy Sellier, Petros Dellaportas; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2769-2791

Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks

Huishuai Zhang, Da Yu, Yiping Lu, Di He; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2792-2804

Nearly Optimal Latent State Decoding in Block MDPs

Yassir Jedra, Junghyun Lee, Alexandre Proutiere, Se-Young Yun; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2805-2904

On the Limitations of the Elo, Real-World Games are Transitive, not Additive

Quentin Bertrand, Wojciech Marian Czarnecki, Gauthier Gidel; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2905-2921

Agnostic PAC Learning of $k$-juntas Using $L_2$-Polynomial Regression

Mohsen Heidari, Wojciech Szpankowski; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2922-2938

Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group

Zhenbang Wang, Emanuel Ben-David, Martin Slawski; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2939-2959

Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems

Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2960-2974

Analysis of Catastrophic Forgetting for Random Orthogonal Transformation Tasks in the Overparameterized Regime

Daniel Goldfarb, Paul Hand; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2975-2993

Clustering above Exponential Families with Tempered Exponential Measures

Ehsan Amid, Richard Nock, Manfred K. Warmuth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2994-3017

Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets

Hussein Hazimeh, Natalia Ponomareva; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3018-3033

Learning Physics-Informed Neural Networks without Stacked Back-propagation

Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3034-3047

An Optimization-based Algorithm for Non-stationary Kernel Bandits without Prior Knowledge

Kihyuk Hong, Yuhang Li, Ambuj Tewari; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3048-3085

Multi-armed Bandit Experimental Design: Online Decision-making and Adaptive Inference

David Simchi-Levi, Chonghuan Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3086-3097

Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits

Wonyoung Kim, Myunghee Cho Paik, Min-Hwan Oh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3098-3124

Byzantine-Robust Federated Learning with Optimal Statistical Rates

Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3151-3178

An Unpooling Layer for Graph Generation

Yinglong Guo, Dongmian Zou, Gilad Lerman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3179-3209

Online Learning for Traffic Routing under Unknown Preferences

Devansh Jalota, Karthik Gopalakrishnan, Navid Azizan, Ramesh Johari, Marco Pavone; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3210-3229

Byzantine-Robust Online and Offline Distributed Reinforcement Learning

Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3230-3269

No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution

Mengxiao Zhang, Shi Chen, Haipeng Luo, Yingfei Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3270-3298

Mode-constrained Model-based Reinforcement Learning via Gaussian Processes

Aidan Scannell, Carl Henrik Ek, Arthur Richards; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3299-3314

Generative Oversampling for Imbalanced Data via Majority-Guided VAE

Qingzhong Ai, Pengyun Wang, Lirong He, Liangjian Wen, Lujia Pan, Zenglin Xu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3315-3330

The Lie-Group Bayesian Learning Rule

Eren Mehmet Kiral, Thomas Moellenhoff, Mohammad Emtiyaz Khan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3331-3352

Singular Value Representation: A New Graph Perspective On Neural Networks

Dan Meller, Nicolas Berkouk; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3353-3369

A Finite Sample Complexity Bound for Distributionally Robust Q-learning

Shengbo Wang, Nian Si, Jose Blanchet, Zhengyuan Zhou; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3370-3398

Connectivity-contrastive learning: Combining causal discovery and representation learning for multimodal data

Hiroshi Morioka, Aapo Hyvarinen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3399-3426

A Bregman Divergence View on the Difference-of-Convex Algorithm

Oisin Faust, Hamza Fawzi, James Saunderson; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3427-3439

Minority Oversampling for Imbalanced Data via Class-Preserving Regularized Auto-Encoders

Arnab Kumar Mondal, Lakshya Singhal, Piyush Tiwary, Parag Singla, Prathosh AP; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3440-3465

T-Phenotype: Discovering Phenotypes of Predictive Temporal Patterns in Disease Progression

Yuchao Qin, Mihaela van der Schaar, Changhee Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3466-3492

Membership Inference Attacks against Synthetic Data through Overfitting Detection

Boris van Breugel, Hao Sun, Zhaozhi Qian, Mihaela van der Schaar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3493-3514

Online Learning for Non-monotone DR-Submodular Maximization: From Full Information to Bandit Feedback

Qixin Zhang, Zengde Deng, Zaiyi Chen, Kuangqi Zhou, Haoyuan Hu, Yu Yang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3515-3537

Robust Variational Autoencoding with Wasserstein Penalty for Novelty Detection

Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3538-3567

To Impute or not to Impute? Missing Data in Treatment Effect Estimation

Jeroen Berrevoets, Fergus Imrie, Trent Kyono, James Jordon, Mihaela van der Schaar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3568-3590

No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities

Sebastian Shenghong Tay, Quoc Phong Nguyen, Chuan Sheng Foo, Bryan Kian Hsiang Low; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3591-3619

Noise-Aware Statistical Inference with Differentially Private Synthetic Data

Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3620-3643

ASkewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks

Louis Leconte, Sholom Schechtman, Eric Moulines; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3644-3663

Transport Elliptical Slice Sampling

Alberto Cabezas, Christopher Nemeth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3664-3676

Towards Balanced Representation Learning for Credit Policy Evaluation

Yiyan Huang, Cheuk Hang Leung, Shumin Ma, Zhiri Yuan, Qi Wu, Siyi Wang, Dongdong Wang, Zhixiang Huang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3677-3692

Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition

Lukang Sun, Avetik Karagulyan, Peter Richtarik; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3693-3717

MARS: Masked Automatic Ranks Selection in Tensor Decompositions

Maxim Kodryan, Dmitry Kropotov, Dmitry Vetrov; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3718-3732

Learning from Multiple Sources for Data-to-Text and Text-to-Data

Song Duong, Alberto Lumbreras, Mike Gartrell, Patrick Gallinari; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3733-3753

Sparse Bayesian optimization

Sulin Liu, Qing Feng, David Eriksson, Benjamin Letham, Eytan Bakshy; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3754-3774

On the bias of K-fold cross validation with stable learners

Anass Aghbalou, Anne Sabourin, François Portier; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3775-3794

Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior

Yohan Jung, Jinkyoo Park; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3795-3824

Sample Efficiency of Data Augmentation Consistency Regularization

Shuo Yang, Yijun Dong, Rachel Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3825-3853

ANACONDA: An Improved Dynamic Regret Algorithm for Adaptive Non-Stationary Dueling Bandits

Thomas Kleine Buening, Aadirupa Saha; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3854-3878

Deep Joint Source-Channel Coding with Iterative Source Error Correction

Changwoo Lee, Xiao Hu, Hun-Seok Kim; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3879-3902

On-Demand Communication for Asynchronous Multi-Agent Bandits

Yu-Zhen Janice Chen, Lin Yang, Xuchuang Wang, Xutong Liu, Mohammad Hajiesmaili, John C. S. Lui, Don Towsley; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3903-3930

The ELBO of Variational Autoencoders Converges to a Sum of Entropies

Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3931-3960

Autoencoded sparse Bayesian in-IRT factorization, calibration, and amortized inference for the Work Disability Functional Assessment Battery

Joshua C. Chang, Carson C. Chow, Julia Porcino; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3961-3976

Provably Efficient Reinforcement Learning via Surprise Bound

Hanlin Zhu, Ruosong Wang, Jason Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4006-4032

FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery

Xinyi Xu, Zhaoxuan Wu, Arun Verma, Chuan Sheng Foo, Bryan Kian Hsiang Low; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4033-4057

Sampling From a Schrödinger Bridge

Austin Stromme; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4058-4067

A Multi-Task Gaussian Process Model for Inferring Time-Varying Treatment Effects in Panel Data

Yehu Chen, Annamaria Prati, Jacob Montgomery, Roman Garnett; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4068-4088

Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models

Naoya Takeishi, Alexandros Kalousis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4089-4100

Active Learning for Single Neuron Models with Lipschitz Non-Linearities

Aarshvi Gajjar, Christopher Musco, Chinmay Hegde; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4101-4113

Exploration in Reward Machines with Low Regret

Hippolyte Bourel, Anders Jonsson, Odalric-Ambrym Maillard, Mohammad Sadegh Talebi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4114-4146

On Universal Portfolios with Continuous Side Information

Alankrita Bhatt, J. Jon Ryu, Young-Han Kim; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4147-4163

Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation

Yaxuan Zhu, Jianwen Xie, Ping Li; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4164-4180

The Lauritzen-Chen Likelihood For Graphical Models

Ilya Shpitser; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4181-4195

Bayesian Strategy-Proof Facility Location via Robust Estimation

Emmanouil Zampetakis, Fred Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4196-4208

Unsupervised representation learning with recognition-parametrised probabilistic models

William I. Walker, Hugo Soulat, Changmin Yu, Maneesh Sahani; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4209-4230

Universal Agent Mixtures and the Geometry of Intelligence

Samuel Allen Alexander, David Quarel, Len Du, Marcus Hutter; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4231-4246

The communication cost of security and privacy in federated frequency estimation

Wei-Ning Chen, Ayfer Ozgur, Graham Cormode, Akash Bharadwaj; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4247-4274

Learning While Scheduling in Multi-Server Systems With Unknown Statistics: MaxWeight with Discounted UCB

Zixian Yang, R. Srikant, Lei Ying; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4275-4312

Piecewise Stationary Bandits under Risk Criteria

Sujay Bhatt, Guanhua Fang, Ping Li; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4313-4335

Does Label Differential Privacy Prevent Label Inference Attacks?

Ruihan Wu, Jin Peng Zhou, Kilian Q. Weinberger, Chuan Guo; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4336-4347

Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data

Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4348-4380

Conjugate Gradient Method for Generative Adversarial Networks

Hiroki Naganuma, Hideaki Iiduka; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4381-4408

Subset verification and search algorithms for causal DAGs

Davin Choo, Kirankumar Shiragur; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4409-4442

Distributed Offline Policy Optimization Over Batch Data

Han Shen, Songtao Lu, Xiaodong Cui, Tianyi Chen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4443-4472

Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling

Rui Wang, Pengyu Cheng, Ricardo Henao; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4473-4485

Learning Sparse Graphon Mean Field Games

Christian Fabian, Kai Cui, Heinz Koeppl; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4486-4514

Temporal Graph Neural Networks for Irregular Data

Joel Oskarsson, Per Sidén, Fredrik Lindsten; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4515-4531

Oblivious near-optimal sampling for multidimensional signals with Fourier constraints

Xingyu Xu, Yuantao Gu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4532-4555

Isotropic Gaussian Processes on Finite Spaces of Graphs

Viacheslav Borovitskiy, Mohammad Reza Karimi, Vignesh Ram Somnath, Andreas Krause; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4556-4574

Mean Parity Fair Regression in RKHS

Shaokui Wei, Jiayin Liu, Bing Li, Hongyuan Zha; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4602-4628

A Unified Perspective on Regularization and Perturbation in Differentiable Subset Selection

Xiangqian Sun, Cheuk Hang Leung, Yijun Li, Qi Wu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4629-4642

Nyström Method for Accurate and Scalable Implicit Differentiation

Ryuichiro Hataya, Makoto Yamada; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4643-4654

Fair Representation Learning with Unreliable Labels

Yixuan Zhang, Feng Zhou, Zhidong Li, Yang Wang, Fang Chen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4655-4667

Neural Discovery of Permutation Subgroups

Pavan Karjol, Rohan Kashyap, Prathosh AP; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4668-4678

Feasible Recourse Plan via Diverse Interpolation

Duy Nguyen, Ngoc Bui, Viet Anh Nguyen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4679-4698

Computing Abductive Explanations for Boosted Trees

Gilles Audemard, Jean-Marie Lagniez, Pierre Marquis, Nicolas Szczepanski; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4699-4711

A Statistical Learning Take on the Concordance Index for Survival Analysis

Kevin Elgui, Alex Nowak, Geneviève Robin; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4712-4731

Equivariant Representation Learning via Class-Pose Decomposition

Giovanni Luca Marchetti, Gustaf Tegnér, Anastasiia Varava, Danica Kragic; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4745-4756

Approximating a RUM from Distributions on $k$-Slates

Flavio Chierichetti, Mirko Giacchini, Ravi Kumar, Alessandro Panconesi, Andrew Tomkins; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4757-4767

Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality

Ikko Yamane, Yann Chevaleyre, Takashi Ishida, Florian Yger; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4768-4801

Coordinate Descent for SLOPE

Johan Larsson, Quentin Klopfenstein, Mathurin Massias, Jonas Wallin; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4802-4821

Multi-task Representation Learning with Stochastic Linear Bandits

Leonardo Cella, Karim Lounici, Grégoire Pacreau, Massimiliano Pontil; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4822-4847

A Sea of Words: An In-Depth Analysis of Anchors for Text Data

Gianluigi Lopardo, Frederic Precioso, Damien Garreau; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4848-4879

High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent

Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4894-4916

On Generalization of Decentralized Learning with Separable Data

Hossein Taheri, Christos Thrampoulidis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4917-4945

Neural Simulated Annealing

Alvaro H.C. Correia, Daniel E. Worrall, Roberto Bondesan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4946-4962

Adaptation to Misspecified Kernel Regularity in Kernelised Bandits

Yusha Liu, Aarti Singh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4963-4985

Gaussian Processes on Distributions based on Regularized Optimal Transport

François Bachoc, Louis Béthune, Alberto Gonzalez-Sanz, Jean-Michel Loubes; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4986-5010

Optimal Contextual Bandits with Knapsacks under Realizability via Regression Oracles

Yuxuan Han, Jialin Zeng, Yang Wang, Yang Xiang, Jiheng Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5011-5035

Bounding Evidence and Estimating Log-Likelihood in VAE

Łukasz Struski, Marcin Mazur, Paweł Batorski, Przemysław Spurek, Jacek Tabor; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5036-5051

Privacy-preserving Sparse Generalized Eigenvalue Problem

Lijie Hu, Zihang Xiang, Jiabin Liu, Di Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5052-5062

Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture

Minh-Toan Nguyen, Romain Couillet; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5063-5078

Manifold Restricted Interventional Shapley Values

Muhammad Faaiz Taufiq, Patrick Blöbaum, Lenon Minorics; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5079-5106

A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization

Yutong Dai, Guanyi Wang, Frank E. Curtis, Daniel P. Robinson; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5107-5133

Complex-to-Real Sketches for Tensor Products with Applications to the Polynomial Kernel

Jonas Wacker, Ruben Ohana, Maurizio Filippone; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5181-5212

Nonmyopic Multiclass Active Search with Diminishing Returns for Diverse Discovery

Quan Nguyen, Roman Garnett; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5231-5249

Efficient fair PCA for fair representation learning

Matthäus Kleindessner, Michele Donini, Chris Russell, Muhammad Bilal Zafar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5250-5270

Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics

Masahiro Kato, Masaaki Imaizumi, Kentaro Minami; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5271-5298

Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms

Vincent Plassier, Eric Moulines, Alain Durmus; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5299-5356

Adversarial Random Forests for Density Estimation and Generative Modeling

David S. Watson, Kristin Blesch, Jan Kapar, Marvin N. Wright; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5357-5375

Smoothly Giving up: Robustness for Simple Models

Tyler Sypherd, Nathaniel Stromberg, Richard Nock, Visar Berisha, Lalitha Sankar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5376-5410

A Tighter Problem-Dependent Regret Bound for Risk-Sensitive Reinforcement Learning

Xiaoyan Hu, Ho-Fung Leung; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5411-5437

Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation

Gandharv Patil, Prashanth L.A., Dheeraj Nagaraj, Doina Precup; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5438-5448

Asymptotically Unbiased Off-Policy Policy Evaluation when Reusing Old Data in Nonstationary Environments

Vincent Liu, Yash Chandak, Philip Thomas, Martha White; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5474-5492

Is interpolation benign for random forest regression?

Ludovic Arnould, Claire Boyer, Erwan Scornet; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5493-5548

TabLLM: Few-shot Classification of Tabular Data with Large Language Models

Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David Sontag; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5549-5581

A Faster Sampler for Discrete Determinantal Point Processes

Simon Barthelmé, Nicolas Tremblay, Pierre-Olivier Amblard; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5582-5592

Faithful Heteroscedastic Regression with Neural Networks

Andrew Stirn, Harm Wessels, Megan Schertzer, Laura Pereira, Neville Sanjana, David Knowles; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5593-5613

Boosted Off-Policy Learning

Ben London, Levi Lu, Ted Sandler, Thorsten Joachims; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5614-5640

Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence

Sarath Pattathil, Kaiqing Zhang, Asuman Ozdaglar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5641-5685

A Contrastive Approach to Online Change Point Detection

Nikita Puchkin, Valeriia Shcherbakova; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5686-5713

Active Membership Inference Attack under Local Differential Privacy in Federated Learning

Truc Nguyen, Phung Lai, Khang Tran, NhatHai Phan, My T. Thai; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5714-5730

Differentially Private Matrix Completion through Low-rank Matrix Factorization

Lingxiao Wang, Boxin Zhao, Mladen Kolar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5731-5748

Private Non-Convex Federated Learning Without a Trusted Server

Andrew Lowy, Ali Ghafelebashi, Meisam Razaviyayn; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5749-5786

Variational Boosted Soft Trees

Tristan Cinquin, Tammo Rukat, Philipp Schmidt, Martin Wistuba, Artur Bekasov; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5787-5801

Cooperative Inverse Decision Theory for Uncertain Preferences

Zachary Robertson, Hantao Zhang, Sanmi Koyejo; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5854-5868

Falsification of Internal and External Validity in Observational Studies via Conditional Moment Restrictions

Zeshan Hussain, Ming-Chieh Shih, Michael Oberst, Ilker Demirel, David Sontag; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5869-5898

Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification

Yuqing Hu, Stephane Pateux, Vincent Gripon; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5899-5917

Heavy Sets with Applications to Interpretable Machine Learning Diagnostics

Dmitry Malioutov, Sanjeeb Dash, Dennis Wei; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5918-5930

Stochastic Mirror Descent for Large-Scale Sparse Recovery

Sasila Ilandarideva, Yannis Bekri, Anatoli Iouditski, Vianney Perchet; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5931-5957

High Probability Bounds for Stochastic Continuous Submodular Maximization

Evan Becker, Jingdong Gao, Ted Zadouri, Baharan Mirzasoleiman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5958-5979

Average Adjusted Association: Efficient Estimation with High Dimensional Confounders

Sung Jae Jun, Sokbae Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5980-5996

Reinforcement Learning for Adaptive Mesh Refinement

Jiachen Yang, Tarik Dzanic, Brenden Petersen, Jun Kudo, Ketan Mittal, Vladimir Tomov, Jean-Sylvain Camier, Tuo Zhao, Hongyuan Zha, Tzanio Kolev, Robert Anderson, Daniel Faissol; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5997-6014

Risk Bounds on Aleatoric Uncertainty Recovery

Yikai Zhang, Jiahe Lin, Fengpei Li, Yeshaya Adler, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6015-6036

Robust and Agnostic Learning of Conditional Distributional Treatment Effects

Nathan Kallus, Miruna Oprescu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6037-6060

Optimism and Delays in Episodic Reinforcement Learning

Benjamin Howson, Ciara Pike-Burke, Sarah Filippi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6061-6094

Delayed Feedback in Generalised Linear Bandits Revisited

Benjamin Howson, Ciara Pike-Burke, Sarah Filippi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6095-6119

Stochastic Tree Ensembles for Estimating Heterogeneous Effects

Nikolay Krantsevich, Jingyu He, P. Richard Hahn; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6120-6131

Minimax Nonparametric Two-Sample Test under Adversarial Losses

Rong Tang, Yun Yang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6132-6165

Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon Forecasting

Helmuth Naumer, Farzad Kamalabadi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6166-6198

Distill n’ Explain: explaining graph neural networks using simple surrogates

Tamara Pereira, Erik Nascimento, Lucas E. Resck, Diego Mesquita, Amauri Souza; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6199-6214

Nonstationary Bandit Learning via Predictive Sampling

Yueyang Liu, Benjamin Van Roy, Kuang Xu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6215-6244

Continuous-Time Decision Transformer for Healthcare Applications

Zhiyue Zhang, Hongyuan Mei, Yanxun Xu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6245-6262

Dueling RL: Reinforcement Learning with Trajectory Preferences

Aadirupa Saha, Aldo Pacchiano, Jonathan Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6263-6289

Discrete Langevin Samplers via Wasserstein Gradient Flow

Haoran Sun, Hanjun Dai, Bo Dai, Haomin Zhou, Dale Schuurmans; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6290-6313

Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion

Haotian Ju, Dongyue Li, Aneesh Sharma, Hongyang R. Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6314-6341

Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning

Volodymyr Tkachuk, Seyed Alireza Bakhtiari, Johannes Kirschner, Matej Jusup, Ilija Bogunovic, Csaba Szepesvári; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6342-6370

NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning

Muralikrishnna G Sethuraman, Romain Lopez, Rahul Mohan, Faramarz Fekri, Tommaso Biancalani, Jan-Christian Huetter; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6371-6387

Revisiting Fair-PAC Learning and the Axioms of Cardinal Welfare

Cyrus Cousins; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6422-6442

Distributionally Robust Policy Gradient for Offline Contextual Bandits

Zhouhao Yang, Yihong Guo, Pan Xu, Anqi Liu, Animashree Anandkumar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6443-6462

A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets

Hideaki Ishibashi, Masayuki Karasuyama, Ichiro Takeuchi, Hideitsu Hino; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6463-6497

LOFT: Finding Lottery Tickets through Filter-wise Training

Qihan Wang, Chen Dun, Fangshuo Liao, Chris Jermaine, Anastasios Kyrillidis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6498-6526

Provably Efficient Model-Free Algorithms for Non-stationary CMDPs

Honghao Wei, Arnob Ghosh, Ness Shroff, Lei Ying, Xingyu Zhou; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6527-6570

Precision Recall Cover: A Method For Assessing Generative Models

Fasil Cheema, Ruth Urner; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6571-6594

Reconstructing Training Data from Model Gradient, Provably

Zihan Wang, Jason Lee, Qi Lei; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6595-6612

Scalable Spectral Clustering with Group Fairness Constraints

Ji Wang, Ding Lu, Ian Davidson, Zhaojun Bai; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6613-6629

Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout

Chen Dun, Mirian Hipolito, Chris Jermaine, Dimitrios Dimitriadis, Anastasios Kyrillidis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6630-6660

Learning with Partial Forgetting in Modern Hopfield Networks

Toshihiro Ota, Ikuro Sato, Rei Kawakami, Masayuki Tanaka, Nakamasa Inoue; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6661-6673

Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection

Weilin Cong, Mehrdad Mahdavi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6674-6703

Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach

Yunzhe Zhou, Zhengling Qi, Chengchun Shi, Lexin Li; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6704-6721

Uncertainty-aware Unsupervised Video Hashing

Yucheng Wang, Mingyuan Zhou, Yu Sun, Xiaoning Qian; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6722-6740

Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach

Vishnu Raj, Tianyu Cui, Markus Heinonen, Pekka Marttinen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6741-6763

Structure of Nonlinear Node Embeddings in Stochastic Block Models

Christopher Harker, Aditya Bhaskara; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6764-6782

On Model Selection Consistency of Lasso for High-Dimensional Ising Models

Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6783-6805

Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition

Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6806-6821

INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation

Ning Liu, Yue Yu, Huaiqian You, Neeraj Tatikola; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6822-6838

Transport Reversible Jump Proposals

Laurence Davies, Robert Salomone, Matthew Sutton, Chris Drovandi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6839-6852

Convex Bounds on the Softmax Function with Applications to Robustness Verification

Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark Barrett, Eitan Farchi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6853-6878

Strong Lottery Ticket Hypothesis with $\varepsilon$–perturbation

Zheyang Xiong, Fangshuo Liao, Anastasios Kyrillidis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6879-6902

Two-Sample Tests for Inhomogeneous Random Graphs in $L_r$ Norm: Optimality and Asymptotics

Sayak Chatterjee, Dibyendu Saha, Soham Dan, Bhaswar B. Bhattacharya; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6903-6911

Differentiable Change-point Detection With Temporal Point Processes

Paramita Koley, Harshavardhan Alimi, Shrey Singla, Sourangshu Bhattacharya, Niloy Ganguly, Abir De; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6940-6955

Recurrent Neural Networks and Universal Approximation of Bayesian Filters

Adrian N. Bishop, Edwin V. Bonilla; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6956-6967

Thresholded linear bandits

Nishant A. Mehta, Junpei Komiyama, Vamsi K. Potluru, Andrea Nguyen, Mica Grant-Hagen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6968-7020

Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings

Aryan Deshwal, Sebastian Ament, Maximilian Balandat, Eytan Bakshy, Janardhan Rao Doppa, David Eriksson; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7021-7039

Unifying local and global model explanations by functional decomposition of low dimensional structures

Munir Hiabu, Joseph T. Meyer, Marvin N. Wright; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7040-7060

SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals

Alexander K. Lew, George Matheos, Tan Zhi-Xuan, Matin Ghavamizadeh, Nishad Gothoskar, Stuart Russell, Vikash K. Mansinghka; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7061-7088

On double-descent in uncertainty quantification in overparametrized models

Lucas Clarte, Bruno Loureiro, Florent Krzakala, Lenka Zdeborova; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7089-7125

Learning Treatment Effects from Observational and Experimental Data

Sofia Triantafillou, Fattaneh Jabbari, Gregory F. Cooper; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7126-7146

On the Accelerated Noise-Tolerant Power Method

Zhiqiang Xu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7147-7175

Clustering High-dimensional Data with Ordered Weighted $\ell_1$ Regularization

Chandramauli Chakraborty, Sayan Paul, Saptarshi Chakraborty, Swagatam Das; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7176-7189

Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracles

Aldo Gael Carranza, Sanath Kumar Krishnamurthy, Susan Athey; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7190-7212

Faster Projection-Free Augmented Lagrangian Methods via Weak Proximal Oracle

Dan Garber, Tsur Livney, Shoham Sabach; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7213-7238

Meta-Learning with Adjoint Methods

Shibo Li, Zheng Wang, Akil Narayan, Robert Kirby, Shandian Zhe; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7239-7251

Combining Graphical and Algebraic Approaches for Parameter Identification in Latent Variable Structural Equation Models

Ankur Ankan, Inge Wortel, Kenneth Bollen, Johannes Textor; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7252-7264

Explicit Regularization in Overparametrized Models via Noise Injection

Antonio Orvieto, Anant Raj, Hans Kersting, Francis Bach; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7265-7287

Efficient Informed Proposals for Discrete Distributions via Newton’s Series Approximation

Yue Xiang, Dongyao Zhu, Bowen Lei, Dongkuan Xu, Ruqi Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7288-7310

An Homogeneous Unbalanced Regularized Optimal Transport Model with Applications to Optimal Transport with Boundary

Theo Lacombe; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7311-7330

Prediction-Oriented Bayesian Active Learning

Freddie Bickford Smith, Andreas Kirsch, Sebastian Farquhar, Yarin Gal, Adam Foster, Tom Rainforth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7331-7348

Active Exploration via Experiment Design in Markov Chains

Mojmir Mutny, Tadeusz Janik, Andreas Krause; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7349-7374

But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI

Charles Marx, Youngsuk Park, Hilaf Hasson, Yuyang Wang, Stefano Ermon, Luke Huan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7375-7391

Identification of Blackwell Optimal Policies for Deterministic MDPs

Victor Boone, Bruno Gaujal; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7392-7424

Multi-Fidelity Bayesian Optimization with Unreliable Information Sources

Petrus Mikkola, Julien Martinelli, Louis Filstroff, Samuel Kaski; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7425-7454

Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback

Fares Fourati, Vaneet Aggarwal, Christopher Quinn, Mohamed-Slim Alouini; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7455-7471

Protecting Global Properties of Datasets with Distribution Privacy Mechanisms

Michelle Chen, Olga Ohrimenko; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7472-7491

Incremental Aggregated Riemannian Gradient Method for Distributed PCA

Xiaolu Wang, Yuchen Jiao, Hoi-To Wai, Yuantao Gu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7492-7510

Minimax-Bayes Reinforcement Learning

Thomas Kleine Buening, Christos Dimitrakakis, Hannes Eriksson, Divya Grover, Emilio Jorge; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7511-7527

Retrospective Uncertainties for Deep Models using Vine Copulas

Natasa Tagasovska, Firat Ozdemir, Axel Brando; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7528-7539

Optimal Algorithms for Latent Bandits with Cluster Structure

Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7540-7577

Improved Bound on Generalization Error of Compressed KNN Estimator

Hang Zhang, Ping Li; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7578-7593

Online Linearized LASSO

Shuoguang Yang, Yuhao Yan, Xiuneng Zhu, Qiang Sun; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7594-7610

Multi-Agent congestion cost minimization with linear function approximations

Prashant Trivedi, Nandyala Hemachandra; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7611-7643

Global-Local Regularization Via Distributional Robustness

Hoang Phan, Trung Le, Trung Phung, Anh Tuan Bui, Nhat Ho, Dinh Phung; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7644-7664

Vector Quantized Time Series Generation with a Bidirectional Prior Model

Daesoo Lee, Sara Malacarne, Erlend Aune; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7665-7693

Risk-aware linear bandits with convex loss

Patrick Saux, Odalric Maillard; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7723-7754

One Arrow, Two Kills: A Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits

Pierre Gaillard, Aadirupa Saha, Soham Dan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7755-7773

Data Augmentation for Imbalanced Regression

Samuel Stocksieker, Denys Pommeret, Arthur Charpentier; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7774-7799

Fast Feature Selection with Fairness Constraints

Francesco Quinzan, Rajiv Khanna, Moshik Hershcovitch, Sarel Cohen, Daniel Waddington, Tobias Friedrich, Michael W. Mahoney; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7800-7823

On the Consistency Rate of Decision Tree Learning Algorithms

Qin-Cheng Zheng, Shen-Huan Lyu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7824-7848

Rank-Based Causal Discovery for Post-Nonlinear Models

Grigor Keropyan, David Strieder, Mathias Drton; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7849-7870

On the Complexity of Representation Learning in Contextual Linear Bandits

Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7871-7896

Hierarchical-Hyperplane Kernels for Actively Learning Gaussian Process Models of Nonstationary Systems

Matthias Bitzer, Mona Meister, Christoph Zimmer; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7897-7912

Revisiting Weighted Strategy for Non-stationary Parametric Bandits

Jing Wang, Peng Zhao, Zhi-Hua Zhou; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7913-7942

No time to waste: practical statistical contact tracing with few low-bit messages

Rob Romijnders, Yuki M. Asano, Christos Louizos, Max Welling; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7943-7960

Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data

Alicia Curth, Mihaela van der Schaar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7961-7980

Beyond Performative Prediction: Open-environment Learning with Presence of Corruptions

Jia-Wei Shan, Peng Zhao, Zhi-Hua Zhou; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7981-7998

Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games

Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Kentaro Toyoshima, Atsushi Iwasaki; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7999-8028

Model-Based Uncertainty in Value Functions

Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8029-8052

The Role of Codeword-to-Class Assignments in Error-Correcting Codes: An Empirical Study

Itay Evron, Ophir Onn, Tamar Weiss, Hai Azeroual, Daniel Soudry; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8053-8077

Online Algorithms with Costly Predictions

Marina Drygala, Sai Ganesh Nagarajan, Ola Svensson; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8078-8101

Adaptive Tuning for Metropolis Adjusted Langevin Trajectories

Lionel Riou-Durand, Pavel Sountsov, Jure Vogrinc, Charles Margossian, Sam Power; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8102-8116

Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits

Taira Tsuchiya, Shinji Ito, Junya Honda; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8117-8144

PAC-Bayesian Learning of Optimization Algorithms

Michael Sucker, Peter Ochs; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8145-8164

Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty

Felix Biggs, Benjamin Guedj; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8165-8182

Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery

Tyler Maunu, Thibaut Le Gouic, Philippe Rigollet; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8183-8210

Pointwise sampling uncertainties on the Precision-Recall curve

Ralph E.Q. Urlus, Max Baak, Stéphane Collot, Ilan Fridman Rojas; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8211-8232

Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference

Debangshu Banerjee, Avishek Ghosh, Sayak Ray Chowdhury, Aditya Gopalan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8233-8262

Nothing but Regrets — Privacy-Preserving Federated Causal Discovery

Osman Mian, David Kaltenpoth, Michael Kamp, Jilles Vreeken; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8263-8278

Nonparametric Gaussian Process Covariances via Multidimensional Convolutions

Thomas M. Mcdonald, Magnus Ross, Michael T. Smith, Mauricio A. Álvarez; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8279-8293

Improved Representation Learning Through Tensorized Autoencoders

Pascal Esser, Satyaki Mukherjee, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8294-8307

Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data

Frederiek Wesel, Kim Batselier; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8308-8320

A Targeted Accuracy Diagnostic for Variational Approximations

Yu Wang, Mikolaj Kasprzak, Jonathan H. Huggins; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8351-8372

Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loops

Charles K. Assaad, Imad Ez-Zejjari, Lei Zan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8395-8404

Principled Approaches for Private Adaptation from a Public Source

Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8405-8432

CLIP-Lite: Information Efficient Visual Representation Learning with Language Supervision

Aman Shrivastava, Ramprasaath R. Selvaraju, Nikhil Naik, Vicente Ordonez; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8433-8447

Surveillance Evasion Through Bayesian Reinforcement Learning

Dongping Qi, David Bindel, Alexander Vladimirsky; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8448-8462

Overparameterized Random Feature Regression with Nearly Orthogonal Data

Zhichao Wang, Yizhe Zhu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8463-8493

How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm?

Haiyun He, Gholamali Aminian, Yuheng Bu, Miguel Rodrigues, Vincent Y. F. Tan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8494-8520

Scalable Unbalanced Sobolev Transport for Measures on a Graph

Tam Le, Truyen Nguyen, Kenji Fukumizu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8521-8560

Discrete Distribution Estimation under User-level Local Differential Privacy

Jayadev Acharya, Yuhan Liu, Ziteng Sun; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8561-8585

Causal Entropy Optimization

Nicola Branchini, Virginia Aglietti, Neil Dhir, Theodoros Damoulas; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8586-8605

Loss-Curvature Matching for Dataset Selection and Condensation

Seungjae Shin, Heesun Bae, Donghyeok Shin, Weonyoung Joo, Il-Chul Moon; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8606-8628

Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints

Kyriakos Lotidis, Nicholas Bambos, Jose Blanchet, Jiajin Li; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8629-8644

Density Ratio Estimation and Neyman Pearson Classification with Missing Data

Josh Givens, Song Liu, Henry W. J. Reeve; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8645-8681

Representation Learning in Deep RL via Discrete Information Bottleneck

Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8699-8722

Learning Robust Graph Neural Networks with Limited Supervision

Abdullah Alchihabi, Yuhong Guo; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8723-8733

Consistent Complementary-Label Learning via Order-Preserving Losses

Shuqi Liu, Yuzhou Cao, Qiaozhen Zhang, Lei Feng, Bo An; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8734-8748

Tight Regret and Complexity Bounds for Thompson Sampling via Langevin Monte Carlo

Tom Huix, Matthew Zhang, Alain Durmus; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8749-8770

Nonstochastic Contextual Combinatorial Bandits

Lukas Zierahn, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Gergely Neu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8771-8813

Probabilistic Conformal Prediction Using Conditional Random Samples

Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David Blei; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8814-8836

Preferential Subsampling for Stochastic Gradient Langevin Dynamics

Srshti Putcha, Christopher Nemeth, Paul Fearnhead; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8837-8856

On the Calibration of Probabilistic Classifier Sets

Thomas Mortier, Viktor Bengs, Eyke Hüllermeier, Stijn Luca, Willem Waegeman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8857-8870

Context-Specific Causal Discovery for Categorical Data Using Staged Trees

Manuele Leonelli, Gherardo Varando; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8871-8888

Federated Learning for Data Streams

Othmane Marfoq, Giovanni Neglia, Laetitia Kameni, Richard Vidal; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8889-8924

Adversarial robustness of VAEs through the lens of local geometry

Asif Khan, Amos Storkey; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8954-8967

Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise

Haotian Ye, James Zou, Linjun Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8968-8990

Learning to Optimize with Stochastic Dominance Constraints

Hanjun Dai, Yuan Xue, Niao He, Yixin Wang, Na Li, Dale Schuurmans, Bo Dai; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8991-9009

SoundSynp: Sound Source Detection from Raw Waveforms with Multi-Scale Synperiodic Filterbanks

Yuhang He, Andrew Markham; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9010-9023

Second Order Path Variationals in Non-Stationary Online Learning

Dheeraj Baby, Yu-Xiang Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9024-9075

Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach

Syrine Belakaria, Janardhan Rao Doppa, Nicolo Fusi, Rishit Sheth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9076-9093

Knowledge Sheaves: A Sheaf-Theoretic Framework for Knowledge Graph Embedding

Thomas Gebhart, Jakob Hansen, Paul Schrater; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9094-9116

Active Cost-aware Labeling of Streaming Data

Ting Cai, Kirthevasan Kandasamy; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9117-9136

Krylov–Bellman boosting: Super-linear policy evaluation in general state spaces

Eric Xia, Martin Wainwright; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9137-9166

SwAMP: Swapped Assignment of Multi-Modal Pairs for Cross-Modal Retrieval

Minyoung Kim; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9167-9190

A Mini-Block Fisher Method for Deep Neural Networks

Achraf Bahamou, Donald Goldfarb, Yi Ren; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9191-9220

On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network

Hongchang Gao, Bin Gu, My T. Thai; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9238-9281

Pricing against a Budget and ROI Constrained Buyer

Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9282-9307

Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining

Nicholas Monath, Manzil Zaheer, Kelsey Allen, Andrew Mccallum; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9308-9330

Incentive-aware Contextual Pricing with Non-parametric Market Noise

Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9331-9361

Coherent Probabilistic Forecasting of Temporal Hierarchies

Syama Sundar Rangapuram, Shubham Kapoor, Rajbir Singh Nirwan, Pedro Mercado, Tim Januschowski, Yuyang Wang, Michael Bohlke-Schneider; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9362-9376

Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems

Nicolas Christianson, Junxuan Shen, Adam Wierman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9377-9399

Randomized geometric tools for anomaly detection in stock markets

Cyril Bachelard, Apostolos Chalkis, Vissarion Fisikopoulos, Elias Tsigaridas; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9400-9416

ForestPrune: Compact Depth-Pruned Tree Ensembles

Brian Liu, Rahul Mazumder; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9417-9428

Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games

Arnab Maiti, Kevin Jamieson, Lillian Ratliff; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9429-9469

Multiple-policy High-confidence Policy Evaluation

Chris Dann, Mohammad Ghavamzadeh, Teodor V. Marinov; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9470-9487

Compositional Probabilistic and Causal Inference using Tractable Circuit Models

Benjie Wang, Marta Kwiatkowska; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9488-9498

Improved Approximation for Fair Correlation Clustering

Sara Ahmadian, Maryam Negahbani; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9499-9516

Diffusion Generative Models in Infinite Dimensions

Gavin Kerrigan, Justin Ley, Padhraic Smyth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9538-9563

MMD-B-Fair: Learning Fair Representations with Statistical Testing

Namrata Deka, Danica J. Sutherland; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9564-9576

Domain Adaptation under Missingness Shift

Helen Zhou, Sivaraman Balakrishnan, Zachary Lipton; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9577-9606

Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games

Maria-Florina Balcan, Rattana Pukdee, Pradeep Ravikumar, Hongyang Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9607-9636

Adapting to Latent Subgroup Shifts via Concepts and Proxies

Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D’Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9637-9661

On the Privacy Risks of Algorithmic Recourse

Martin Pawelczyk, Himabindu Lakkaraju, Seth Neel; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9680-9696

Reducing Discretization Error in the Frank-Wolfe Method

Zhaoyue Chen, Yifan Sun; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9697-9727

Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning

Zaiyan Xu, Kishan Panaganti, Dileep Kalathil; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9728-9754

Factorial SDE for Multi-Output Gaussian Process Regression

Daniel P. Jeong, Seyoung Kim; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9755-9772

Interactive Learning with Pricing for Optimal and Stable Allocations in Markets

Yigit Efe Erginbas, Soham Phade, Kannan Ramchandran; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9773-9806

Learning to Generalize Provably in Learning to Optimize

Junjie Yang, Tianlong Chen, Mingkang Zhu, Fengxiang He, Dacheng Tao, Yingbin Liang, Zhangyang Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9807-9825

Theory and Algorithm for Batch Distribution Drift Problems

Pranjal Awasthi, Corinna Cortes, Christopher Mohri; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9826-9851

On The Convergence Of Policy Iteration-Based Reinforcement Learning With Monte Carlo Policy Evaluation

Anna Winnicki, R. Srikant; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9852-9878

Precision/Recall on Imbalanced Test Data

Hongwei Shang, Jean-Marc Langlois, Kostas Tsioutsiouliklis, Changsung Kang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9879-9891

Iterative Teaching by Data Hallucination

Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9892-9913

Near-Optimal Differentially Private Reinforcement Learning

Dan Qiao, Yu-Xiang Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9914-9940

Doubly Fair Dynamic Pricing

Jianyu Xu, Dan Qiao, Yu-Xiang Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9941-9975

Probabilities of Causation: Role of Observational Data

Ang Li, Judea Pearl; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10012-10027

Influence Diagnostics under Self-concordance

Jillian Fisher, Lang Liu, Krishna Pillutla, Yejin Choi, Zaid Harchaoui; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10028-10076

Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness

Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10077-10094

Large deviations rates for stochastic gradient descent with strongly convex functions

Dragana Bajovic, Dusan Jakovetic, Soummya Kar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10095-10111

Stochastic Optimization for Spectral Risk Measures

Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaid Harchaoui; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10112-10159

Improving Adaptive Conformal Prediction Using Self-Supervised Learning

Nabeel Seedat, Alan Jeffares, Fergus Imrie, Mihaela van der Schaar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10160-10177

Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path

Muhammad Aneeq Uz Zaman, Alec Koppel, Sujay Bhatt, Tamer Basar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10178-10206

Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck

Anirban Samaddar, Sandeep Madireddy, Prasanna Balaprakash, Taps Maiti, Gustavo de los Campos, Ian Fischer; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10207-10222

Ideal Abstractions for Decision-Focused Learning

Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10223-10234

Probabilistic Querying of Continuous-Time Event Sequences

Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10235-10251

Semantic Strengthening of Neuro-Symbolic Learning

Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10252-10261

Fast Variational Estimation of Mutual Information for Implicit and Explicit Likelihood Models

Caleb Dahlke, Sue Zheng, Jason Pacheco; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10262-10278

SurvivalGAN: Generating Time-to-Event Data for Survival Analysis

Alexander Norcliffe, Bogdan Cebere, Fergus Imrie, Pietro Lió, Mihaela van der Schaar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10279-10304

A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem

Ruichen Jiang, Nazanin Abolfazli, Aryan Mokhtari, Erfan Yazdandoost Hamedani; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10305-10323

Stochastic Methods for AUC Optimization subject to AUC-based Fairness Constraints

Yao Yao, Qihang Lin, Tianbao Yang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10324-10342

DIET: Conditional independence testing with marginal dependence measures of residual information

Mukund Sudarshan, Aahlad Puli, Wesley Tansey, Rajesh Ranganath; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10343-10367

Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain Adaptation

Qi Chen, Mario Marchand; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10368-10394

Actually Sparse Variational Gaussian Processes

Harry Jake Cunningham, Daniel Augusto de Souza, So Takao, Mark van der Wilk, Marc Peter Deisenroth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10395-10408

Competing against Adaptive Strategies in Online Learning via Hints

Aditya Bhaskara, Kamesh Munagala; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10409-10424

ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images

Matthew D. Hoffman, Tuan Anh Le, Pavel Sountsov, Christopher Suter, Ben Lee, Vikash K. Mansinghka, Rif A. Saurous; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10425-10444

Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier

Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan Greenewald, Murat Kocaoglu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10445-10469

Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions

Kaiqi Zhao, Animesh Jain, Ming Zhao; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10470-10486

Sample Complexity of Distinguishing Cause from Effect

Jayadev Acharya, Sourbh Bhadane, Arnab Bhattacharyya, Saravanan Kandasamy, Ziteng Sun; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10487-10504

Graph Spectral Embedding using the Geodesic Betweenness Centrality

Shay Deutsch, Stefano Soatto; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10505-10519

Score-based Quickest Change Detection for Unnormalized Models

Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10546-10565

Dropout-Resilient Secure Multi-Party Collaborative Learning with Linear Communication Complexity

Xingyu Lu, Hasin Us Sami, Başak Güler; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10566-10593

Reinforcement Learning with Stepwise Fairness Constraints

Zhun Deng, He Sun, Steven Wu, Linjun Zhang, David Parkes; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10594-10618

Federated Asymptotics: a model to compare federated learning algorithms

Gary Cheng, Karan Chadha, John Duchi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10650-10689

Conformalized Unconditional Quantile Regression

Ahmed M. Alaa, Zeshan Hussain, David Sontag; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10690-10702

Wasserstein Distributional Learning via Majorization-Minimization

Chengliang Tang, Nathan Lenssen, Ying Wei, Tian Zheng; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10703-10731

HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent

Ziang Chen, Jianfeng Lu, Huajie Qian, Xinshang Wang, Wotao Yin; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10732-10781

Ultra-marginal Feature Importance: Learning from Data with Causal Guarantees

Joseph Janssen, Vincent Guan, Elina Robeva; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10782-10814

On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data

Tina Behnia, Ganesh Ramachandra Kini, Vala Vakilian, Christos Thrampoulidis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10815-10838

Convolutional Persistence as a Remedy to Neural Model Analysis

Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10839-10855

Uniformly Conservative Exploration in Reinforcement Learning

Wanqiao Xu, Yecheng Ma, Kan Xu, Hamsa Bastani, Osbert Bastani; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10856-10870

Provable Safe Reinforcement Learning with Binary Feedback

Andrew Bennett, Dipendra Misra, Nathan Kallus; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10871-10900

Balanced Off-Policy Evaluation for Personalized Pricing

Adam Elmachtoub, Vishal Gupta, Yunfan Zhao; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10901-10917

Provable Hierarchy-Based Meta-Reinforcement Learning

Kurtland Chua, Qi Lei, Jason Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10918-10967

A Blessing of Dimensionality in Membership Inference through Regularization

Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10968-10993

Posterior Tracking Algorithm for Classification Bandits

Koji Tabata, Junpei Komiyama, Atsuyoshi Nakamura, Tamiki Komatsuzaki; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10994-11022

Mixtures of All Trees

Nikil Roashan Selvam, Honghua Zhang, Guy Van den Broeck; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11043-11058

Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection Classes

Sina Baharlouei, Fatemeh Sheikholeslami, Meisam Razaviyayn, Zico Kolter; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11059-11078

Performative Prediction with Neural Networks

Mehrnaz Mofakhami, Ioannis Mitliagkas, Gauthier Gidel; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11079-11093

Benign overfitting of non-smooth neural networks beyond lazy training

Xingyu Xu, Yuantao Gu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11094-11117

A New Modeling Framework for Continuous, Sequential Domains

Hailiang Dong, James Amato, Vibhav Gogate, Nicholas Ruozzi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11118-11131

TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation

Jackie Baek, Vivek Farias; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11132-11148

Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws

Kush Bhatia, Wenshuo Guo, Jacob Steinhardt; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11149-11171

Approximate Regions of Attraction in Learning with Decision-Dependent Distributions

Roy Dong, Heling Zhang, Lillian Ratliff; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11172-11184

Randomized Primal-Dual Methods with Adaptive Step Sizes

Erfan Yazdandoost Hamedani, Afrooz Jalilzadeh, Necdet S. Aybat; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11185-11212

Spectral Augmentations for Graph Contrastive Learning

Amur Ghose, Yingxue Zhang, Jianye Hao, Mark Coates; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11213-11266

Deep Value Function Networks for Large-Scale Multistage Stochastic Programs

Hyunglip Bae, Jinkyu Lee, Woo Chang Kim, Yongjae Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11267-11287

Optimal Sketching Bounds for Sparse Linear Regression

Tung Mai, Alexander Munteanu, Cameron Musco, Anup Rao, Chris Schwiegelshohn, David Woodruff; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11288-11316

Average case analysis of Lasso under ultra sparse conditions

Koki Okajima, Xiangming Meng, Takashi Takahashi, Yoshiyuki Kabashima; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11317-11330

Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition

Sebastian Gruber, Florian Buettner; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11331-11354

Collision Probability Matching Loss for Disentangling Epistemic Uncertainty from Aleatoric Uncertainty

Hiromi Narimatsu, Mayuko Ozawa, Shiro Kumano; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11355-11370

Random Features Model with General Convex Regularization: A Fine Grained Analysis with Precise Asymptotic Learning Curves

David Bosch, Ashkan Panahi, Ayca Ozcelikkale, Devdatt Dubhashi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11371-11414

Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles

Rajeev Verma, Daniel Barrejon, Eric Nalisnick; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11415-11434

Spread Flows for Manifold Modelling

Mingtian Zhang, Yitong Sun, Chen Zhang, Steven Mcdonagh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11435-11456

Breaking a Classical Barrier for Classifying Arbitrary Test Examples in the Quantum Model

Grzegorz Gluch, Khashayar Barooti, Rüdiger Urbanke; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11457-11488

Characterizing Polarization in Social Networks using the Signed Relational Latent Distance Model

Nikolaos Nakis, Abdulkadir Celikkanat, Louis Boucherie, Christian Djurhuus, Felix Burmester, Daniel Mathias Holmelund, Monika Frolcová, Morten Mørup; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11489-11505

Algorithm for Constrained Markov Decision Process with Linear Convergence

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Inducing Neural Collapse in Deep Long-tailed Learning

Xuantong Liu, Jianfeng Zhang, Tianyang Hu, He Cao, Yuan Yao, Lujia Pan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11534-11544

Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity

Arber Qoku, Florian Buettner; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11545-11562

Regression as Classification: Influence of Task Formulation on Neural Network Features

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Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond

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Probing Graph Representations

Mohammad Sadegh Akhondzadeh, Vijay Lingam, Aleksandar Bojchevski; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11630-11649

Efficient SAGE Estimation via Causal Structure Learning

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