ICML 2022

1,233 papers

To Smooth or Not? When Label Smoothing Meets Noisy Labels

Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Masashi Sugiyama

More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize

Alexander Wei, Wei Hu, Jacob Steinhardt

Certifying Out-of-Domain Generalization for Blackbox Functions

Maurice G Weber, Linyi Li, Boxin Wang, Zhikuan Zhao, Bo Li

Policy Gradient Method For Robust Reinforcement Learning

Yue Wang, Shaofeng Zou

Thompson Sampling for (Combinatorial) Pure Exploration

Siwei Wang, Jun Zhu

Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition

Zheng Wang, Shandian Zhe

Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition

Haotao Wang, Aston Zhang, Yi Zhu, Shuai Zheng, Mu Li

Removing Batch Normalization Boosts Adversarial Training

Haotao Wang, Aston Zhang, Shuai Zheng, Xingjian SHI, Mu Li

Individual Reward Assisted Multi-Agent Reinforcement Learning

Li Wang, Yupeng Zhang, Yujing Hu, Weixun Wang, Chongjie Zhang

Thompson Sampling for Robust Transfer in Multi-Task Bandits

Zhi Wang, Chicheng Zhang, Kamalika Chaudhuri

How Powerful are Spectral Graph Neural Networks

Xiyuan Wang, Muhan Zhang

OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

Peng Wang, An Yang, Rui Men, Junyang Lin, Shuai Bai

Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications

Bokun Wang, Tianbao Yang

DRAGONN: Distributed Randomized Approximate Gradients of Neural Networks

Zhuang Wang, Zhaozhuo Xu, Xinyu Wu, Anshumali Shrivastava, T. S. Eugene Ng

When Are Linear Stochastic Bandits Attackable?

Huazheng Wang, Haifeng Xu, Hongning Wang

Nonparametric Embeddings of Sparse High-Order Interaction Events

Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan

Generative Coarse-Graining of Molecular Conformations

Wujie Wang, Minkai Xu, Chen Cai, Benjamin K Miller, Tess Smidt

Multiple-Play Stochastic Bandits with Shareable Finite-Capacity Arms

Xuchuang Wang, Hong Xie, John C. S. Lui

Causal Dynamics Learning for Task-Independent State Abstraction

Zizhao Wang, Xuesu Xiao, Zifan Xu, Yuke Zhu, Peter Stone

Tractable Uncertainty for Structure Learning

Benjie Wang, Matthew R Wicker, Marta Kwiatkowska

Understanding Instance-Level Impact of Fairness Constraints

Jialu Wang, Xin Eric Wang, Yang Liu

Three-stage Evolution and Fast Equilibrium for SGD with Non-degerate Critical Points

Yi Wang, Zhiren Wang

Approximately Equivariant Networks for Imperfectly Symmetric Dynamics

Rui Wang, Robin Walters, Rose Yu

Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models and Amortized Policy Search

Qi Wang, Herke van Hoof

ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training

Hui-Po Wang, Sebastian Stich, Yang He, Mario Fritz

Provable Domain Generalization via Invariant-Feature Subspace Recovery

Haoxiang Wang, Haozhe Si, Bo Li, Han Zhao

Risk-Averse No-Regret Learning in Online Convex Games

Zifan Wang, Yi Shen, Michael Zavlanos

Improving Task-free Continual Learning by Distributionally Robust Memory Evolution

Zhenyi Wang, Li Shen, Le Fang, Qiuling Suo, Tiehang Duan

What Language Model Architecture and Pretraining Objective Works Best for Zero-Shot Generalization?

Thomas Wang, Adam Roberts, Daniel Hesslow, Teven Le Scao, Hyung Won Chung

Iterative Double Sketching for Faster Least-Squares Optimization

Rui Wang, Yanyan Ouyang, Wangli Xu

NP-Match: When Neural Processes meet Semi-Supervised Learning

Jianfeng Wang, Thomas Lukasiewicz, Daniela Massiceti, Xiaolin Hu, Vladimir Pavlovic

Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering

Peng Wang, Huikang Liu, Anthony Man-Cho So, Laura Balzano

Robustness Verification for Contrastive Learning

Zekai Wang, Weiwei Liu

Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out

Jun-Kun Wang, Chi-Heng Lin, Andre Wibisono, Bin Hu

Communication-Efficient Adaptive Federated Learning

Yujia Wang, Lu Lin, Jinghui Chen

Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond

Haoxiang Wang, Bo Li, Han Zhao

Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation

Wenxiao Wang, Alexander J Levine, Soheil Feizi

What Dense Graph Do You Need for Self-Attention?

Yuxin Wang, Chu-Tak Lee, Qipeng Guo, Zhangyue Yin, Yunhua Zhou

The Geometry of Robust Value Functions

KAIXIN WANG, Navdeep Kumar, Kuangqi Zhou, Bryan Hooi, Jiashi Feng

Improving Screening Processes via Calibrated Subset Selection

Lequn Wang, Thorsten Joachims, Manuel Gomez Rodriguez

DynaMixer: A Vision MLP Architecture with Dynamic Mixing

Ziyu Wang, Wenhao Jiang, Yiming M Zhu, Li Yuan, Yibing Song

VLMixer: Unpaired Vision-Language Pre-training via Cross-Modal CutMix

Teng Wang, Wenhao Jiang, Zhichao Lu, Feng Zheng, Ran Cheng

Solving Stackelberg Prediction Game with Least Squares Loss via Spherically Constrained Least Squares Reformulation

Jiali Wang, Wen Huang, Rujun Jiang, Xudong Li, Alex L Wang

Disentangling Disease-related Representation from Obscure for Disease Prediction

Chu-ran Wang, Fei Gao, Fandong Zhang, Fangwei Zhong, Yizhou Yu

Robust Models Are More Interpretable Because Attributions Look Normal

Zifan Wang, Matt Fredrikson, Anupam Datta

Neural Implicit Dictionary Learning via Mixture-of-Expert Training

Peihao Wang, Zhiwen Fan, Tianlong Chen, Zhangyang Wang

Denoised MDPs: Learning World Models Better Than the World Itself

Tongzhou Wang, Simon Du, Antonio Torralba, Phillip Isola, Amy Zhang

Accelerating Shapley Explanation via Contributive Cooperator Selection

Guanchu Wang, Yu-Neng Chuang, Mengnan Du, Fan Yang, Quan Zhou

Fast Lossless Neural Compression with Integer-Only Discrete Flows

Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang

Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods

Yi Wan, Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Sarath Chandar

Greedy based Value Representation for Optimal Coordination in Multi-agent Reinforcement Learning

Lipeng Wan, Zeyang Liu, Xingyu Chen, Xuguang Lan, Nanning Zheng

Safe Exploration for Efficient Policy Evaluation and Comparison

Runzhe Wan, Branislav Kveton, Rui Song

Retroformer: Pushing the Limits of End-to-end Retrosynthesis Transformer

Yue Wan, Chang-Yu Hsieh, Ben Liao, Shengyu Zhang

Training Characteristic Functions with Reinforcement Learning: XAI-methods play Connect Four

Stephan Wäldchen, Sebastian Pokutta, Felix Huber

Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes

Andrew J Wagenmaker, Yifang Chen, Max Simchowitz, Simon Du, Kevin Jamieson

First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach

Andrew J Wagenmaker, Yifang Chen, Max Simchowitz, Simon Du, Kevin Jamieson

Provably Adversarially Robust Nearest Prototype Classifiers

Václav Voráček, Matthias Hein

Multirate Training of Neural Networks

Tiffany J Vlaar, Benedict Leimkuhler

What Can Linear Interpolation of Neural Network Loss Landscapes Tell Us?

Tiffany J Vlaar, Jonathan Frankle

Hermite Polynomial Features for Private Data Generation

Margarita Vinaroz, Mohammad-Amin Charusaie, Frederik Harder, Kamil Adamczewski, Mi Jung Park

Bayesian Nonparametrics for Offline Skill Discovery

Valentin Villecroze, Harry Braviner, Panteha Naderian, Chris Maddison, Gabriel Loaiza-Ganem

Addressing Optimism Bias in Sequence Modeling for Reinforcement Learning

Adam R Villaflor, Zhe Huang, Swapnil Pande, John M Dolan, Jeff Schneider

Multiclass learning with margin: exponential rates with no bias-variance trade-off

Stefano Vigogna, Giacomo Meanti, Ernesto De Vito, Lorenzo Rosasco

On Implicit Bias in Overparameterized Bilevel Optimization

Paul Vicol, Jonathan P Lorraine, Fabian Pedregosa, David Duvenaud, Roger B Grosse

Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation

Daniel Vial, Advait Parulekar, Sanjay Shakkottai, R Srikant

Calibrated Learning to Defer with One-vs-All Classifiers

Rajeev Verma, Eric Nalisnick

VarScene: A Deep Generative Model for Realistic Scene Graph Synthesis

Tathagat Verma, Abir De, Yateesh Agrawal, Vishwa Vinay, Soumen Chakrabarti

Bayesian Optimization under Stochastic Delayed Feedback

Arun Verma, Zhongxiang Dai, Bryan Kian Hsiang Low

Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing

Ramji Venkataramanan, Kevin Kögler, Marco Mondelli

Bregman Power k-Means for Clustering Exponential Family Data

Adithya Vellal, Saptarshi Chakraborty, Jason Q Xu

The CLRS Algorithmic Reasoning Benchmark

Petar Veličković, Adrià Puigdomènech Badia, David Budden, Razvan Pascanu, Andrea Banino

Correlation Clustering via Strong Triadic Closure Labeling: Fast Approximation Algorithms and Practical Lower Bounds

Nate Veldt

Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent

Sharan Vaswani, Benjamin Dubois-Taine, Reza Babanezhad

EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning

Shay Vargaftik, Ran Ben Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben Itzhak

Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning

Sattar Vakili, Jonathan Scarlett, Da-shan Shiu, Alberto Bernacchia

Path-Gradient Estimators for Continuous Normalizing Flows

Lorenz Vaitl, Kim Andrea Nicoli, Shinichi Nakajima, Pan Kessel

Self-Supervised Models of Audio Effectively Explain Human Cortical Responses to Speech

Aditya R Vaidya, Shailee Jain, Alexander Huth

Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures

Nelson Vadori, Rahul Savani, Thomas Spooner, Sumitra Ganesh

Prototype Based Classification from Hierarchy to Fairness

Mycal Tucker, Julie A. Shah

Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding

Kazuma K Tsuji, Ken’Ichiro Tanaka, Sebastian Pokutta

FriendlyCore: Practical Differentially Private Aggregation

Eliad Tsfadia, Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer

Interpretable Off-Policy Learning via Hyperbox Search

Daniel Tschernutter, Tobias Hatt, Stefan Feuerriegel

Fenrir: Physics-Enhanced Regression for Initial Value Problems

Filip Tronarp, Nathanael Bosch, Philipp Hennig

Tackling covariate shift with node-based Bayesian neural networks

Trung Q Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski

A Completely Tuning-Free and Robust Approach to Sparse Precision Matrix Estimation

Chau Tran, Guo Yu

Nesterov Accelerated Shuffling Gradient Method for Convex Optimization

Trang H Tran, Katya Scheinberg, Lam M Nguyen

Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them

Florian Tramer

AnyMorph: Learning Transferable Polices By Inferring Agent Morphology

Brandon Trabucco, Mariano Phielipp, Glen Berseth

Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization

Brandon Trabucco, XINYANG GENG, Aviral Kumar, Sergey Levine

Simple and near-optimal algorithms for hidden stratification and multi-group learning

Christopher J Tosh, Daniel Hsu

A Temporal-Difference Approach to Policy Gradient Estimation

Samuele Tosatto, Andrew Patterson, Martha White, Rupam Mahmood

Quantifying and Learning Linear Symmetry-Based Disentanglement

Loek Tonnaer, Luis Armando Perez Rey, Vlado Menkovski, Mike Holenderski, Jim Portegies

Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data

Umberto M Tomasini, Antonio Sclocchi, Matthieu Wyart

Generic Coreset for Scalable Learning of Monotonic Kernels: Logistic Regression, Sigmoid and more

Elad Tolochinksy, Ibrahim Jubran, Dan Feldman

Object Permanence Emerges in a Random Walk along Memory

Pavel Tokmakov, Allan Jabri, Jie Li, Adrien Gaidon

Extended Unconstrained Features Model for Exploring Deep Neural Collapse

Tom Tirer, Joan Bruna

Deciphering Lasso-based Classification Through a Large Dimensional Analysis of the Iterative Soft-Thresholding Algorithm

Malik Tiomoko, Ekkehard Schnoor, Mohamed El Amine Seddik, Igor Colin, Aladin Virmaux

Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes

Conor Tillinghast, Zheng Wang, Shandian Zhe

From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses

Daniil Tiapkin, Denis Belomestny, Eric Moulines, Alexey Naumov, Sergey Samsonov

On the Finite-Time Complexity and Practical Computation of Approximate Stationarity Concepts of Lipschitz Functions

Lai Tian, Kaiwen Zhou, Anthony Man-Cho So