ICML 2022

1,233 papers

SpaceMAP: Visualizing High-Dimensional Data by Space Expansion

Xinrui Zu, Qian Tao

Counterfactual Prediction for Outcome-Oriented Treatments

Hao Zou, Bo Li, Jiangang Han, Shuiping Chen, Xuetao Ding

Inductive Matrix Completion: No Bad Local Minima and a Fast Algorithm

Pini Zilber, Boaz Nadler

Towards Uniformly Superhuman Autonomy via Subdominance Minimization

Brian Ziebart, Sanjiban Choudhury, Xinyan Yan, Paul Vernaza

Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features

Zhaowei Zhu, Jialu Wang, Yang Liu

Region-Based Semantic Factorization in GANs

Jiapeng Zhu, Yujun Shen, Yinghao Xu, Deli Zhao, Qifeng Chen

Residual-Based Sampling for Online Outlier-Robust PCA

Tianhao Zhu, Jie Shen

Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces

Yinglun Zhu, Paul Mineiro

When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee

Dixian Zhu, Gang Li, Bokun Wang, Xiaodong Wu, Tianbao Yang

On Numerical Integration in Neural Ordinary Differential Equations

Aiqing Zhu, Pengzhan Jin, Beibei Zhu, Yifa Tang

Resilient and Communication Efficient Learning for Heterogeneous Federated Systems

Zhuangdi Zhu, Junyuan Hong, Steve Drew, Jiayu Zhou

Topology-aware Generalization of Decentralized SGD

Tongtian Zhu, Fengxiang He, Lan Zhang, Zhengyang Niu, Mingli Song

Neural-Symbolic Models for Logical Queries on Knowledge Graphs

Zhaocheng Zhu, Mikhail Galkin, Zuobai Zhang, Jian Tang

Contextual Bandits with Large Action Spaces: Made Practical

Yinglun Zhu, Dylan J Foster, John Langford, Paul Mineiro

Detecting Corrupted Labels Without Training a Model to Predict

Zhaowei Zhu, Zihao Dong, Yang Liu

VLUE: A Multi-Task Multi-Dimension Benchmark for Evaluating Vision-Language Pre-training

Wangchunshu Zhou, Yan Zeng, SHIZHE DIAO, Xinsong Zhang

Understanding The Robustness in Vision Transformers

Daquan Zhou, Zhiding Yu, Enze Xie, Chaowei Xiao, Animashree Anandkumar

Contrastive Learning with Boosted Memorization

Zhihan Zhou, Jiangchao Yao, Yan-Feng Wang, Bo Han, Ya Zhang

Modeling Adversarial Noise for Adversarial Training

Dawei Zhou, Nannan Wang, Bo Han, Tongliang Liu

Improving Adversarial Robustness via Mutual Information Estimation

Dawei Zhou, Nannan Wang, Xinbo Gao, Bo Han, Xiaoyu Wang

Approximate Frank-Wolfe Algorithms over Graph-structured Support Sets

Baojian Zhou, Yifan Sun

Probabilistic Bilevel Coreset Selection

Xiao Zhou, Renjie Pi, Weizhong Zhang, Yong Lin, Zonghao Chen

FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting

Tian Zhou, Ziqing MA, Qingsong Wen, xue wang, Liang Sun

Prototype-Anchored Learning for Learning with Imperfect Annotations

Xiong Zhou, Xianming Liu, Deming Zhai, Junjun Jiang, Xin Gao

Sparse Invariant Risk Minimization

Xiao Zhou, Yong Lin, Weizhong Zhang, Tong Zhang

Model Agnostic Sample Reweighting for Out-of-Distribution Learning

Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu

On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features

Jinxin Zhou, Xiao Li, Tianyu Ding, Chong You, Qing Qu

A Hierarchical Bayesian Approach to Inverse Reinforcement Learning with Symbolic Reward Machines

Weichao Zhou, Wenchao Li

Dimension-free Complexity Bounds for High-order Nonconvex Finite-sum Optimization

Dongruo Zhou, Quanquan Gu

Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets

Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang

Describing Differences between Text Distributions with Natural Language

Ruiqi Zhong, Charlie Snell, Dan Klein, Jacob Steinhardt

HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning

Andrey Zhmoginov, Mark Sandler, Maksym Vladymyrov

Learning Efficient and Robust Ordinary Differential Equations via Invertible Neural Networks

Weiming Zhi, Tin Lai, Lionel Ott, Edwin V. Bonilla, Fabio Ramos

Online Decision Transformer

Qinqing Zheng, Amy Zhang, Aditya Grover

Linear Complexity Randomized Self-attention Mechanism

Lin Zheng, Chong Wang, Lingpeng Kong

Ripple Attention for Visual Perception with Sub-quadratic Complexity

Lin Zheng, Huijie Pan, Lingpeng Kong

Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning

Yang Zhao, Hao Zhang, Xiuyuan Hu

Efficient Learning for AlphaZero via Path Consistency

Dengwei Zhao, Shikui Tu, Lei Xu

Certified Robustness Against Natural Language Attacks by Causal Intervention

Haiteng Zhao, Chang Ma, Xinshuai Dong, Anh Tuan Luu, Zhi-Hong Deng

Global Optimization Networks

Sen Zhao, Erez Louidor, Maya Gupta

Learning from Counterfactual Links for Link Prediction

Tong Zhao, Gang Liu, Daheng Wang, Wenhao Yu, Meng Jiang

Learning to Solve PDE-constrained Inverse Problems with Graph Networks

Qingqing Zhao, David B Lindell, Gordon Wetzstein

Dynamic Regret of Online Markov Decision Processes

Peng Zhao, Long-Fei Li, Zhi-Hua Zhou

Toward Compositional Generalization in Object-Oriented World Modeling

Linfeng Zhao, Lingzhi Kong, Robin Walters, Lawson L.S. Wong

NysADMM: faster composite convex optimization via low-rank approximation

Shipu Zhao, Zachary Frangella, Madeleine Udell

PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance

Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He

No-Regret Learning in Time-Varying Zero-Sum Games

Mengxiao Zhang, Peng Zhao, Haipeng Luo, Zhi-Hua Zhou

ROCK: Causal Inference Principles for Reasoning about Commonsense Causality

Jiayao Zhang, Hongming Zhang, Weijie Su, Dan Roth

Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory

Ruiqi Zhang, Xuezhou Zhang, Chengzhuo Ni, Mengdi Wang

Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization

Yihua Zhang, Guanhua Zhang, Prashant Khanduri, Mingyi Hong, Shiyu Chang

Building Robust Ensembles via Margin Boosting

Dinghuai Zhang, Hongyang Zhang, Aaron Courville, Yoshua Bengio, Pradeep Ravikumar

Uncertainty Modeling in Generative Compressed Sensing

Yilang Zhang, Mengchu Xu, Xiaojun Mao, Jian Wang

Expression might be enough: representing pressure and demand for reinforcement learning based traffic signal control

Liang Zhang, Qiang Wu, Jun Shen, Linyuan Lü, Bo Du

Low-Precision Stochastic Gradient Langevin Dynamics

Ruqi Zhang, Andrew Gordon Wilson, Christopher De Sa

A Simple yet Universal Strategy for Online Convex Optimization

Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang

A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks

Huan Zhang, Shiqi Wang, Kaidi Xu, Yihan Wang, Suman Jana

Learning to Estimate and Refine Fluid Motion with Physical Dynamics

Mingrui Zhang, Jianhong Wang, James B Tlhomole, Matthew Piggott

Set Norm and Equivariant Skip Connections: Putting the Deep in Deep Sets

Lily Zhang, Veronica Tozzo, John Higgins, Rajesh Ranganath

Partial Counterfactual Identification from Observational and Experimental Data

Junzhe Zhang, Jin Tian, Elias Bareinboim

Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach

Xuezhou Zhang, Yuda Song, Masatoshi Uehara, Mengdi Wang, Alekh Agarwal

Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations

Michael Zhang, Nimit S Sohoni, Hongyang R Zhang, Chelsea Finn, Christopher Re

NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning

Wentao Zhang, Zeang Sheng, Mingyu Yang, Yang Li, Yu Shen

Making Linear MDPs Practical via Contrastive Representation Learning

Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph Gonzalez, Dale Schuurmans

Neurotoxin: Durable Backdoors in Federated Learning

Zhengming Zhang, Ashwinee Panda, Linyue Song, Yaoqing Yang, Michael Mahoney

Generative Flow Networks for Discrete Probabilistic Modeling

Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron Courville

Rich Feature Construction for the Optimization-Generalization Dilemma

Jianyu Zhang, David Lopez-paz, Léon Bottou

A Langevin-like Sampler for Discrete Distributions

Ruqi Zhang, Xingchao Liu, Qiang Liu

Deep and Flexible Graph Neural Architecture Search

Wentao Zhang, Zheyu Lin, Yu Shen, Yang Li, Zhi Yang

Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity

Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie

Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective

Jingzhao Zhang, Haochuan Li, Suvrit Sra, Ali Jadbabaie

Federated Learning with Label Distribution Skew via Logits Calibration

Jie Zhang, Zhiqi Li, Bo Li, Jianghe Xu, Shuang Wu

Personalized Federated Learning via Variational Bayesian Inference

Xu Zhang, Yinchuan Li, Wenpeng Li, Kaiyang Guo, Yunfeng Shao

Dynamic Topic Models for Temporal Document Networks

Delvin Ce Zhang, Hady Lauw

Role-based Multiplex Network Embedding

Hegui Zhang, Gang Kou

Fairness Interventions as (Dis)Incentives for Strategic Manipulation

Xueru Zhang, Mohammad Mahdi Khalili, Kun Jin, Parinaz Naghizadeh, mingyan liu

GALAXY: Graph-based Active Learning at the Extreme

Jifan Zhang, Julian Katz-Samuels, Robert Nowak

A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms

Xinwei Zhang, Mingyi Hong, Sairaj Dhople, Nicola Elia

Revisiting End-to-End Speech-to-Text Translation From Scratch

Biao Zhang, Barry Haddow, Rico Sennrich

Examining Scaling and Transfer of Language Model Architectures for Machine Translation

Biao Zhang, Behrooz Ghorbani, Ankur Bapna, Yong Cheng, Xavier Garcia

UAST: Uncertainty-Aware Siamese Tracking

Dawei Zhang, Yanwei Fu, Zhonglong Zheng

When and How Mixup Improves Calibration

Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou

Stochastic Continuous Submodular Maximization: Boosting via Non-oblivious Function

Qixin Zhang, Zengde Deng, Zaiyi Chen, Haoyuan Hu, Yu Yang

PDE-Based Optimal Strategy for Unconstrained Online Learning

Zhiyu Zhang, Ashok Cutkosky, Ioannis Paschalidis

Collaboration of Experts: Achieving 80% Top-1 Accuracy on ImageNet with 100M FLOPs

Yikang Zhang, Zhuo Chen, Zhao Zhong

Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy

Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Steven Wu, Jinfeng Yi

Anytime Information Cascade Popularity Prediction via Self-Exciting Processes

Xi Zhang, Akshay Aravamudan, Georgios C Anagnostopoulos

Position Prediction as an Effective Pretraining Strategy

Shuangfei Zhai, Navdeep Jaitly, Jason Ramapuram, Dan Busbridge, Tatiana Likhomanenko

Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts

Yan Zeng, Xinsong Zhang, Hang Li

Efficient PAC Learning from the Crowd with Pairwise Comparisons

Shiwei Zeng, Jie Shen

Multi Resolution Analysis (MRA) for Approximate Self-Attention

Zhanpeng Zeng, Sourav Pal, Jeffery Kline, Glenn M Fung, Vikas Singh

Stabilizing Q-learning with Linear Architectures for Provable Efficient Learning

Andrea Zanette, Martin Wainwright

Actor-Critic based Improper Reinforcement Learning

Mohammadi Zaki, Avi Mohan, Aditya Gopalan, Shie Mannor

Adaptive Conformal Predictions for Time Series

Margaux Zaffran, Olivier Feron, Yannig Goude, Julie Josse, Aymeric Dieuleveut

Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images

Shiran Zada, Itay Benou, Michal Irani

Time Is MattEr: Temporal Self-supervision for Video Transformers

Sukmin Yun, Jaehyung Kim, Dongyoon Han, Hwanjun Song, Jung-Woo Ha

Neural Tangent Kernel Empowered Federated Learning

Kai Yue, Richeng Jin, Ryan Pilgrim, Chau-Wai Wong, Dror Baron

Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance

Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang

Robust Task Representations for Offline Meta-Reinforcement Learning via Contrastive Learning

Haoqi Yuan, Zongqing Lu

Predicting Out-of-Distribution Error with the Projection Norm

Yaodong Yu, Zitong Yang, Alexander Wei, Yi Ma, Jacob Steinhardt

Latent Diffusion Energy-Based Model for Interpretable Text Modelling

Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang