ICML 2021

1,183 papers

Addressing Catastrophic Forgetting in Few-Shot Problems

Pauching Yap, Hippolyt Ritter, David Barber

Deep Learning for Functional Data Analysis with Adaptive Basis Layers

Junwen Yao, Jonas Mueller, Jane-Ling Wang

Improving Generalization in Meta-learning via Task Augmentation

Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian

HAWQ-V3: Dyadic Neural Network Quantization

Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu

SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks

Lingxiao Yang, Ru-Yuan Zhang, Lida Li, Xiaohua Xie

Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural Networks

Yukun Yang, Wenrui Zhang, Peng Li

Delving into Deep Imbalanced Regression

Yuzhe Yang, Kaiwen Zha, Yingcong Chen, Hao Wang, Dina Katabi

Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss

Xue Yang, Junchi Yan, Qi Ming, Wentao Wang, XIAOPENG ZHANG

When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC

Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao

Voice2Series: Reprogramming Acoustic Models for Time Series Classification

Chao-Han Huck Yang, Yun-Yun Tsai, Pin-Yu Chen

Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies

Tsung-Yen Yang, Justinian Rosca, Karthik Narasimhan, Peter J Ramadge

Representation Matters: Offline Pretraining for Sequential Decision Making

Mengjiao Yang, Ofir Nachum

Graph Neural Networks Inspired by Classical Iterative Algorithms

Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan

Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics

Greg Yang, Etai Littwin

BASGD: Buffered Asynchronous SGD for Byzantine Learning

Yi-Rui Yang, Wu-jun Li

LARNet: Lie Algebra Residual Network for Face Recognition

Xiaolong Yang, Xiaohong Jia, Dihong Gong, Dong-Ming Yan, Zhifeng Li

Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks

Greg Yang, Edward J. Hu

Learning Optimal Auctions with Correlated Valuations from Samples

Chunxue Yang, Xiaohui Bei

Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models

Zitong Yang, Yu Bai, Song Mei

CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection

Hanshu Yan, Jingfeng ZHANG, Gang Niu, Jiashi Feng, Vincent Tan

On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Framework

Zeyu Yan, Fei Wen, Rendong Ying, Chao Ma, Peilin Liu

CATE: Computation-aware Neural Architecture Encoding with Transformers

Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang

Link Prediction with Persistent Homology: An Interactive View

Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen

EL-Attention: Memory Efficient Lossless Attention for Generation

Yu Yan, Jiusheng Chen, Weizhen Qi, Nikhil Bhendawade, Yeyun Gong

Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences

Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama

Structured Convolutional Kernel Networks for Airline Crew Scheduling

Yassine Yaakoubi, Francois Soumis, Simon Lacoste-Julien

KNAS: Green Neural Architecture Search

Jingjing Xu, Liang Zhao, Junyang Lin, Rundong Gao, Xu Sun

Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings

Kan Xu, Xuanyi Zhao, Hamsa Bastani, Osbert Bastani

Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth

Keyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi

Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality

Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang

Learner-Private Convex Optimization

Jiaming Xu, Kuang Xu, Dana Yang

Conformal prediction interval for dynamic time-series

Chen Xu, Yao Xie

Self-supervised Graph-level Representation Learning with Local and Global Structure

Minghao Xu, Hang Wang, Bingbing Ni, Hongyu Guo, Jian Tang

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming

Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio

Dash: Semi-Supervised Learning with Dynamic Thresholding

Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yu-feng Li

Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives

Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, Kannan Achan

Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold

Wenkai Xu, Takeru Matsuda

To be Robust or to be Fair: Towards Fairness in Adversarial Training

Han Xu, Xiaorui Liu, Yaxin Li, Anil Jain, Jiliang Tang

CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee

Tengyu Xu, Yingbin Liang, Guanghui Lan

Explore Visual Concept Formation for Image Classification

Shengzhou Xiong, Yihua Tan, Guoyou Wang

A Hybrid Variance-Reduced Method for Decentralized Stochastic Non-Convex Optimization

Ran Xin, Usman Khan, Soummya Kar

Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization

Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama

Learning While Playing in Mean-Field Games: Convergence and Optimality

Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca

Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization

Sang Michael Xie, Tengyu Ma, Percy Liang

Interaction-Grounded Learning

Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad

Batch Value-function Approximation with Only Realizability

Tengyang Xie, Nan Jiang

Deep Reinforcement Learning amidst Continual Structured Non-Stationarity

Annie Xie, James Harrison, Chelsea Finn

RNNRepair: Automatic RNN Repair via Model-based Analysis

Xiaofei Xie, Wenbo Guo, Lei Ma, Wei Le, Jian Wang

CRFL: Certifiably Robust Federated Learning against Backdoor Attacks

Chulin Xie, Minghao Chen, Pin-Yu Chen, Bo Li

On the Optimality of Batch Policy Optimization Algorithms

Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore

A Bit More Bayesian: Domain-Invariant Learning with Uncertainty

Zehao Xiao, Jiayi Shen, Xiantong Zhen, Ling Shao, Cees Snoek

Data-efficient Hindsight Off-policy Option Learning

Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki

Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach

Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Junchi Yan, Hongyuan Zha

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M Susskind, Jian Zhang

Generative Video Transformer: Can Objects be the Words?

Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn

On Reinforcement Learning with Adversarial Corruption and Its Application to Block MDP

Tianhao Wu, Yunchang Yang, Simon Du, Liwei Wang

Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels

Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong

Temporally Correlated Task Scheduling for Sequence Learning

Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu

ChaCha for Online AutoML

Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi

LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning

Yuhuai Wu, Markus N Rabe, Wenda Li, Jimmy Ba, Roger B Grosse

Making Paper Reviewing Robust to Bid Manipulation Attacks

Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten

Conjugate Energy-Based Models

Hao Wu, Babak Esmaeili, Michael Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent

Learning Neural Network Subspaces

Mitchell Wortsman, Maxwell C Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari

Leveraging Sparse Linear Layers for Debuggable Deep Networks

Eric Wong, Shibani Santurkar, Aleksander Madry

Leveraging Language to Learn Program Abstractions and Search Heuristics

Lionel Wong, Kevin M Ellis, Joshua Tenenbaum, Jacob Andreas

Prediction-Centric Learning of Independent Cascade Dynamics from Partial Observations

Mateusz Wilinski, Andrey Lokhov

Which transformer architecture fits my data? A vocabulary bottleneck in self-attention

Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua

Composing Normalizing Flows for Inverse Problems

Jay Whang, Erik Lindgren, Alex Dimakis

Solving Inverse Problems with a Flow-based Noise Model

Jay Whang, Qi Lei, Alex Dimakis

Learning de-identified representations of prosody from raw audio

Jack Weston, Raphael Lenain, Udeepa Meepegama, Emil Fristed

Keyframe-Focused Visual Imitation Learning

Chuan Wen, Jierui Lin, Jianing Qian, Yang Gao, Dinesh Jayaraman

Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning

Zixin Wen, Yuanzhi Li

Characterizing the Gap Between Actor-Critic and Policy Gradient

Junfeng Wen, Saurabh Kumar, Ramki Gummadi, Dale Schuurmans

Leveraged Weighted Loss for Partial Label Learning

Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang

Thinking Like Transformers

Gail Weiss, Yoav Goldberg, Eran Yahav

A Structured Observation Distribution for Generative Biological Sequence Prediction and Forecasting

Eli N Weinstein, Debora Marks

Meta-learning Hyperparameter Performance Prediction with Neural Processes

Ying Wei, Peilin Zhao, Junzhou Huang

Inferring serial correlation with dynamic backgrounds

Song Wei, Yao Xie, Dobromir Rahnev

Decision-Making Under Selective Labels: Optimal Finite-Domain Policies and Beyond

Dennis Wei

A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention

Tomoki Watanabe, Paolo Favaro

Robust Asymmetric Learning in POMDPs

Andrew Warrington, Jonathan W Lavington, Adam Scibior, Mark Schmidt, Frank Wood

Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing

KAIXIN WANG, Kuangqi Zhou, Qixin Zhang, Jie Shao, Bryan Hooi

Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation

Haoxiang Wang, Han Zhao, Bo Li

Guarantees for Tuning the Step Size using a Learning-to-Learn Approach

Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge

Evolving Attention with Residual Convolutions

Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai

Learning to Weight Imperfect Demonstrations

Yunke Wang, Chang Xu, Bo Du, Honglak Lee

Instabilities of Offline RL with Pre-Trained Neural Representation

Ruosong Wang, Yifan Wu, Ruslan Salakhutdinov, Sham Kakade

UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data

Chengyi Wang, Yu Wu, Yao Qian, Kenichi Kumatani, Shujie LIU

Matrix Completion with Model-free Weighting

Jiayi Wang, Raymond K. W. Wong, Xiaojun Mao, Kwun Chuen Gary Chan

Quantum algorithms for reinforcement learning with a generative model

Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler

SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II

Xiangjun Wang, Junxiao Song, Penghui Qi, Peng Peng, Zhenkun Tang

An exact solver for the Weston-Watkins SVM subproblem

Yutong Wang, Clayton Scott

Directional Bias Amplification

Angelina Wang, Olga Russakovsky

SketchEmbedNet: Learning Novel Concepts by Imitating Drawings

Alexander Wang, Mengye Ren, Richard Zemel

Robust Learning for Data Poisoning Attacks

Yunjuan Wang, Poorya Mianjy, Raman Arora

The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks

Bohan Wang, Qi Meng, Wei Chen, Tie-yan Liu

ConvexVST: A Convex Optimization Approach to Variance-stabilizing Transformation

Mengfan Wang, Boyu Lyu, Guoqiang Yu

Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method

Peng Wang, Huikang Liu, Zirui Zhou, Anthony Man-Cho So

A Modular Analysis of Provable Acceleration via Polyak’s Momentum: Training a Wide ReLU Network and a Deep Linear Network

Jun-Kun Wang, Chi-Heng Lin, Jacob D Abernethy

Robust Inference for High-Dimensional Linear Models via Residual Randomization

Y. Samuel Wang, Si Kai Lee, Panos Toulis, Mladen Kolar