ICML 2022

1,233 papers

Multi-slots Online Matching with High Entropy

Xingyu Lu, Qintong Wu, Wenliang Zhong

Model-Free Opponent Shaping

Christopher Lu, Timon Willi, Christian A Schroeder De Witt, Jakob Foerster

ModLaNets: Learning Generalisable Dynamics via Modularity and Physical Inductive Bias

Yupu Lu, Shijie Lin, Guanqi Chen, Jia Pan

Additive Gaussian Processes Revisited

Xiaoyu Lu, Alexis Boukouvalas, James Hensman

A Single-Loop Gradient Descent and Perturbed Ascent Algorithm for Nonconvex Functional Constrained Optimization

Songtao Lu

Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension

Bruno Loureiro, Cedric Gerbelot, Maria Refinetti, Gabriele Sicuro, Florent Krzakala

Feature Learning and Signal Propagation in Deep Neural Networks

Yizhang Lou, Chris E Mingard, Soufiane Hayou

Bayesian Model Selection, the Marginal Likelihood, and Generalization

Sanae Lotfi, Pavel Izmailov, Gregory Benton, Micah Goldblum, Andrew Gordon Wilson

AutoIP: A United Framework to Integrate Physics into Gaussian Processes

Da Long, Zheng Wang, Aditi Krishnapriyan, Robert Kirby, Shandian Zhe

On the Impossibility of Learning to Cooperate with Adaptive Partner Strategies in Repeated Games

Robert Loftin, Frans A Oliehoek

Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy Optimization

Minghuan Liu, Zhengbang Zhu, Yuzheng Zhuang, Weinan Zhang, Jianye Hao

Robust Training under Label Noise by Over-parameterization

Sheng Liu, Zhihui Zhu, Qing Qu, Chong You

GACT: Activation Compressed Training for Generic Network Architectures

Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen

Learning from Demonstration: Provably Efficient Adversarial Policy Imitation with Linear Function Approximation

Zhihan Liu, Yufeng Zhang, Zuyue Fu, Zhuoran Yang, Zhaoran Wang

Asking for Knowledge (AFK): Training RL Agents to Query External Knowledge Using Language

Iou-Jen Liu, Xingdi Yuan, Marc-Alexandre Côté, Pierre-yves Oudeyer, Alexander Schwing

Local Augmentation for Graph Neural Networks

Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu

Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits

Qinghua Liu, Yuanhao Wang, Chi Jin

Kill a Bird with Two Stones: Closing the Convergence Gaps in Non-Strongly Convex Optimization by Directly Accelerated SVRG with Double Compensation and Snapshots

Yuanyuan Liu, Fanhua Shang, Weixin An, Hongying Liu, Zhouchen Lin

REvolveR: Continuous Evolutionary Models for Robot-to-robot Policy Transfer

Xingyu Liu, Deepak Pathak, Kris Kitani

Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction

Zijian Liu, Ta Duy Nguyen, Alina Ene, Huy Nguyen

Communication-efficient Distributed Learning for Large Batch Optimization

Rui Liu, Barzan Mozafari

Generating 3D Molecules for Target Protein Binding

Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, Shuiwang Ji

Welfare Maximization in Competitive Equilibrium: Reinforcement Learning for Markov Exchange Economy

Zhihan Liu, Miao Lu, Zhaoran Wang, Michael Jordan, Zhuoran Yang

Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning

Chang Liu, Chenfei Lou, Runzhong Wang, Alan Yuhan Xi, Li Shen

Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training

Risheng Liu, Xuan Liu, Shangzhi Zeng, Jin Zhang, YIXUAN ZHANG

Rethinking Attention-Model Explainability through Faithfulness Violation Test

Yibing Liu, Haoliang Li, Yangyang Guo, Chenqi Kong, Jing Li

Simplex Neural Population Learning: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games

Siqi Liu, Marc Lanctot, Luke Marris, Nicolas Heess

Gating Dropout: Communication-efficient Regularization for Sparsely Activated Transformers

Rui Liu, Young Jin Kim, Alexandre Muzio, Hany Hassan

Deep Probability Estimation

Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan

Equivalence Analysis between Counterfactual Regret Minimization and Online Mirror Descent

Weiming Liu, Huacong Jiang, Bin Li, Houqiang Li

Boosting Graph Structure Learning with Dummy Nodes

Xin Liu, Jiayang Cheng, Yangqiu Song, Xin Jiang

Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint

Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang

Constrained Variational Policy Optimization for Safe Reinforcement Learning

ZUXIN LIU, Zhepeng Cen, Vladislav Isenbaev, Wei Liu, Steven Wu

Distributionally Robust Q-Learning

Zijian Liu, Qinxun Bai, Jose Blanchet, Perry Dong, Wei Xu

StreamingQA: A Benchmark for Adaptation to New Knowledge over Time in Question Answering Models

Adam Liska, Tomas Kocisky, Elena Gribovskaya, Tayfun Terzi, Eren Sezener

CITRIS: Causal Identifiability from Temporal Intervened Sequences

Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen

Delayed Reinforcement Learning by Imitation

Pierre Liotet, Davide Maran, Lorenzo Bisi, Marcello Restelli

Interactively Learning Preference Constraints in Linear Bandits

David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause

Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments

Jinkun Lin, Anqi Zhang, Mathias Lécuyer, Jinyang Li, Aurojit Panda

Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback

Tianyi Lin, Aldo Pacchiano, Yaodong Yu, Michael Jordan

Learning Augmented Binary Search Trees

Honghao Lin, Tian Luo, David Woodruff

Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks

Weiran Lin, Keane Lucas, Lujo Bauer, Michael K. Reiter, Mahmood Sharif

Unsupervised Flow-Aligned Sequence-to-Sequence Learning for Video Restoration

Jing Lin, Xiaowan Hu, Yuanhao Cai, Haoqian Wang, Youliang Yan

Decentralized Online Convex Optimization in Networked Systems

Yiheng Lin, Judy Gan, Guannan Qu, Yash Kanoria, Adam Wierman

Federated Learning with Positive and Unlabeled Data

Xinyang Lin, Hanting Chen, Yixing Xu, Chao Xu, Xiaolin Gui

Flow-Guided Sparse Transformer for Video Deblurring

Jing Lin, Yuanhao Cai, Xiaowan Hu, Haoqian Wang, Youliang Yan

Order Constraints in Optimal Transport

Yu Chin Fabian Lim, Laura Wynter, Shiau Hong Lim

TSPipe: Learn from Teacher Faster with Pipelines

Hwijoon Lim, Yechan Kim, Sukmin Yun, Jinwoo Shin, Dongsu Han

Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks

Litian Liang, Yaosheng Xu, Stephen Mcaleer, Dailin Hu, Alexander Ihler

Exploring and Exploiting Hubness Priors for High-Quality GAN Latent Sampling

Yuanbang Liang, Jing Wu, Yu-Kun Lai, Yipeng Qin

Fat–Tailed Variational Inference with Anisotropic Tail Adaptive Flows

Feynman Liang, Michael Mahoney, Liam Hodgkinson

Finding Global Homophily in Graph Neural Networks When Meeting Heterophily

Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo

Learning Multiscale Transformer Models for Sequence Generation

Bei Li, Tong Zheng, Yi Jing, Chengbo Jiao, Tong Xiao

HousE: Knowledge Graph Embedding with Householder Parameterization

Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang

Double Sampling Randomized Smoothing

Linyi Li, Jiawei Zhang, Tao Xie, Bo Li

Hessian-Free High-Resolution Nesterov Acceleration For Sampling

Ruilin Li, Hongyuan Zha, Molei Tao

Permutation Search of Tensor Network Structures via Local Sampling

CHAO LI, Junhua Zeng, Zerui Tao, Qibin Zhao

Private Adaptive Optimization with Side information

Tian Li, Manzil Zaheer, Sashank Reddi, Virginia Smith

Difference Advantage Estimation for Multi-Agent Policy Gradients

Yueheng Li, Guangming Xie, Zongqing Lu

Let Invariant Rationale Discovery Inspire Graph Contrastive Learning

Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He

Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling

Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong

CerDEQ: Certifiable Deep Equilibrium Model

Mingjie Li, Yisen Wang, Zhouchen Lin

PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration

Pengyi Li, Hongyao Tang, Tianpei Yang, Xiaotian Hao, Tong Sang

MetAug: Contrastive Learning via Meta Feature Augmentation

Jiangmeng Li, Wenwen Qiang, Changwen Zheng, Bing Su, Hui Xiong

High Probability Guarantees for Nonconvex Stochastic Gradient Descent with Heavy Tails

Shaojie Li, Yong Liu

Achieving Fairness at No Utility Cost via Data Reweighing with Influence

Peizhao Li, Hongfu Liu

Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the $O(ε^-7/4)$ Complexity

Huan Li, Zhouchen Lin

BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

Junnan Li, DONGXU LI, Caiming Xiong, Steven Hoi

C-MinHash: Improving Minwise Hashing with Circulant Permutation

Xiaoyun Li, Ping Li

Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning

Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen

PLATINUM: Semi-Supervised Model Agnostic Meta-Learning using Submodular Mutual Information

Changbin Li, Suraj Kothawade, Feng Chen, Rishabh Iyer

Neural Inverse Transform Sampler

Henry Li, Yuval Kluger

Decomposing Temporal High-Order Interactions via Latent ODEs

Shibo Li, Robert Kirby, Shandian Zhe

G$^2$CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters

Mingjie Li, Xiaojun Guo, Yifei Wang, Yisen Wang, Zhouchen Lin

Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning

Yunfei Li, Tian Gao, Jiaqi Yang, Huazhe Xu, Yi Wu

On the Finite-Time Performance of the Knowledge Gradient Algorithm

Yanwen Li, Siyang Gao

On Convergence of Gradient Descent Ascent: A Tight Local Analysis

Haochuan Li, Farzan Farnia, Subhro Das, Ali Jadbabaie

An Analytical Update Rule for General Policy Optimization

Hepeng Li, Nicholas Clavette, Haibo He

Spatial-Channel Token Distillation for Vision MLPs

Yanxi Li, Xinghao Chen, Minjing Dong, Yehui Tang, Yunhe Wang

Robust Training of Neural Networks Using Scale Invariant Architectures

Zhiyuan Li, Srinadh Bhojanapalli, Manzil Zaheer, Sashank Reddi, Sanjiv Kumar

A Simple Unified Framework for High Dimensional Bandit Problems

Wenjie Li, Adarsh Barik, Jean Honorio

Generalized Strategic Classification and the Case of Aligned Incentives

Sagi Levanon, Nir Rosenfeld

Supervised Learning with General Risk Functionals

Liu Leqi, Audrey Huang, Zachary Lipton, Kamyar Azizzadenesheli

Model Selection in Batch Policy Optimization

Jonathan Lee, George Tucker, Ofir Nachum, Bo Dai

Why the Rich Get Richer? On the Balancedness of Random Partition Models

Changwoo J Lee, Huiyan Sang

Least Squares Estimation using Sketched Data with Heteroskedastic Errors

Sokbae Lee, Serena Ng

Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian Optimization

Deokjae Lee, Seungyong Moon, Junhyeok Lee, Hyun Oh Song

Maslow’s Hammer in Catastrophic Forgetting: Node Re-Use vs. Node Activation

Sebastian Lee, Stefano Sarao Mannelli, Claudia Clopath, Sebastian Goldt, Andrew Saxe

Statistical inference with implicit SGD: proximal Robbins-Monro vs. Polyak-Ruppert

Yoonhyung Lee, Sungdong Lee, Joong-Ho Won

Low-Complexity Deep Convolutional Neural Networks on Fully Homomorphic Encryption Using Multiplexed Parallel Convolutions

Eunsang Lee, Joon-Woo Lee, Junghyun Lee, Young-Sik Kim, Yongjune Kim

A Statistical Manifold Framework for Point Cloud Data

Yonghyeon LEE, Seungyeon Kim, Jinwon Choi, Frank Park

Confidence Score for Source-Free Unsupervised Domain Adaptation

Jonghyun Lee, Dahuin Jung, Junho Yim, Sungroh Yoon

Dataset Condensation with Contrastive Signals

Saehyung Lee, Sanghyuk Chun, Sangwon Jung, Sangdoo Yun, Sungroh Yoon

Neural Tangent Kernel Analysis of Deep Narrow Neural Networks

Jongmin Lee, Joo Young Choi, Ernest K Ryu, Albert No

A Random Matrix Analysis of Data Stream Clustering: Coping With Limited Memory Resources

Hugo Lebeau, Romain Couillet, Florent Chatelain

Convergence of Policy Gradient for Entropy Regularized MDPs with Neural Network Approximation in the Mean-Field Regime

James-Michael Leahy, Bekzhan Kerimkulov, David Siska, Lukasz Szpruch

Neurocoder: General-Purpose Computation Using Stored Neural Programs

Hung Le, Svetha Venkatesh

Entropic Gromov-Wasserstein between Gaussian Distributions

Khang Le, Dung Q Le, Huy Nguyen, Dat Do, Tung Pham

Differentially Private Maximal Information Coefficients

John Lazarsfeld, Aaron Johnson, Emmanuel Adeniran

Implicit Bias of Linear Equivariant Networks

Hannah Lawrence, Kristian Georgiev, Andrew Dienes, Bobak T. Kiani