ICLR 2022

1,094 papers

Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space

Yaohua Wang, Yaobin Zhang, Fangyi Zhang, Senzhang Wang, Ming Lin

Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification

Wensi Tang, Guodong Long, LU LIU, Tianyi Zhou, Michael Blumenstein

Focus on the Common Good: Group Distributional Robustness Follows

Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi

Generative Modeling with Optimal Transport Maps

Litu Rout, Alexander Korotin, Evgeny Burnaev

Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings

Dongsheng Wang, Dan dan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth

Discovering Invariant Rationales for Graph Neural Networks

Yingxin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua

Acceleration of Federated Learning with Alleviated Forgetting in Local Training

Chencheng Xu, Zhiwei Hong, Minlie Huang, Tao Jiang

Towards Model Agnostic Federated Learning Using Knowledge Distillation

Andrei Afonin, Sai Praneeth Karimireddy

miniF2F: a cross-system benchmark for formal Olympiad-level mathematics

Kunhao Zheng, Jesse Michael Han, Stanislas Polu

A Unified Wasserstein Distributional Robustness Framework for Adversarial Training

Anh Tuan Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Phung

GiraffeDet: A Heavy-Neck Paradigm for Object Detection

Yiqi Jiang, Zhiyu Tan, Junyan Wang, Xiuyu Sun, Ming Lin

Generative Models as a Data Source for Multiview Representation Learning

Ali Jahanian, Xavier Puig, Yonglong Tian, Phillip Isola

Graph-based Nearest Neighbor Search in Hyperbolic Spaces

Liudmila Prokhorenkova, Dmitry Baranchuk, Nikolay Bogachev, Yury Demidovich, Alexander Kolpakov

Task-Induced Representation Learning

Jun Yamada, Karl Pertsch, Anisha Gunjal, Joseph J Lim

Learning Versatile Neural Architectures by Propagating Network Codes

Mingyu Ding, Yuqi Huo, Haoyu Lu, Linjie Yang, Zhe Wang

LEARNING GUARANTEES FOR GRAPH CONVOLUTIONAL NETWORKS ON THE STOCHASTIC BLOCK MODEL

Wei Lu

RvS: What is Essential for Offline RL via Supervised Learning?

Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine

On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning

Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik

Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL

Bogdan Mazoure, Ahmed M Ahmed, R Devon Hjelm, Andrey Kolobov, Patrick MacAlpine

Do deep networks transfer invariances across classes?

Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George J. Pappas

Self-ensemble Adversarial Training for Improved Robustness

Hongjun Wang, Yisen Wang

Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice

Peihao Wang, Wenqing Zheng, Tianlong Chen, Zhangyang Wang

Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification

Bing Su, Ji-Rong Wen

Deep AutoAugment

Yu Zheng, Zhi Zhang, Shen Yan, Mi Zhang

Active Hierarchical Exploration with Stable Subgoal Representation Learning

Siyuan Li, Jin Zhang, Jianhao Wang, Yang Yu, Chongjie Zhang

A NON-PARAMETRIC REGRESSION VIEWPOINT : GENERALIZATION OF OVERPARAMETRIZED DEEP RELU NETWORK UNDER NOISY OBSERVATIONS

Namjoon Suh, Hyunouk Ko, Xiaoming Huo

Robust Unlearnable Examples: Protecting Data Privacy Against Adversarial Learning

Shaopeng Fu, Fengxiang He, Yang Liu, Li Shen, Dacheng Tao

CrossMatch: Cross-Classifier Consistency Regularization for Open-Set Single Domain Generalization

Ronghang Zhu, Sheng Li

Sparsity Winning Twice: Better Robust Generalization from More Efficient Training

Tianlong Chen, Zhenyu Zhang, pengjun wang, Santosh Balachandra, Haoyu Ma

Topological Experience Replay

Zhang-Wei Hong, Tao Chen, Yen-Chen Lin, Joni Pajarinen, Pulkit Agrawal

Environment Predictive Coding for Visual Navigation

Santhosh Kumar Ramakrishnan, Tushar Nagarajan, Ziad Al-Halah, Kristen Grauman

Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm

Yangguang Li, Feng Liang, Lichen Zhao, Yufeng Cui, Wanli Ouyang

Pseudo Numerical Methods for Diffusion Models on Manifolds

Luping Liu, Yi Ren, Zhijie Lin, Zhou Zhao

Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning

Seanie Lee, Hae Beom Lee, Juho Lee, Sung Ju Hwang

Symbolic Learning to Optimize: Towards Interpretability and Scalability

Wenqing Zheng, Tianlong Chen, Ting-Kuei Hu, Zhangyang Wang

Dynamic Token Normalization improves Vision Transformers

Wenqi Shao, Yixiao Ge, Zhaoyang Zhang, Xuyuan Xu, Xiaogang Wang

Multi-Task Processes

Donggyun Kim, Seongwoong Cho, Wonkwang Lee, Seunghoon Hong

Post-Training Detection of Backdoor Attacks for Two-Class and Multi-Attack Scenarios

Zhen Xiang, David Miller, George Kesidis

Model-augmented Prioritized Experience Replay

Youngmin Oh, Jinwoo Shin, Eunho Yang, Sung Ju Hwang

Huber Additive Models for Non-stationary Time Series Analysis

Yingjie Wang, Xianrui Zhong, Fengxiang He, Hong Chen, Dacheng Tao

PoNet: Pooling Network for Efficient Token Mixing in Long Sequences

Chao-Hong Tan, Qian Chen, Wen Wang, Qinglin Zhang, Siqi Zheng

Auto-Transfer: Learning to Route Transferable Representations

Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen

A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion

Zhaoyang Lyu, Zhifeng Kong, Xudong XU, Liang Pan, Dahua Lin

Zero Pixel Directional Boundary by Vector Transform

Edoardo Mello Rella, Ajad Chhatkuli, Yun Liu, Ender Konukoglu, Luc Van Gool

FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes

David W. Romero, Robert-Jan Bruintjes, Jakub Mikolaj Tomczak, Erik J Bekkers, Mark Hoogendoorn

iFlood: A Stable and Effective Regularizer

Yuexiang Xie, Zhen Wang, Yaliang Li, Ce Zhang, Jingren Zhou

Unraveling Model-Agnostic Meta-Learning via The Adaptation Learning Rate

Yingtian Zou, Fusheng Liu, Qianxiao Li

HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning

Ziniu Li, Yingru Li, Yushun Zhang, Tong Zhang, Zhi-Quan Luo

Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity

Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar

Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How

Yuning You, Yue Cao, Tianlong Chen, Zhangyang Wang, Yang Shen

LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning

David Henry Mguni, Taher Jafferjee, Jianhong Wang, Nicolas Perez-Nieves, Oliver Slumbers

Anomaly Detection for Tabular Data with Internal Contrastive Learning

Tom Shenkar, Lior Wolf

Unsupervised Disentanglement with Tensor Product Representations on the Torus

Michael Rotman, Amit Dekel, Shir Gur, Yaron Oz, Lior Wolf

Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning

Jakub Grudzien Kuba, Ruiqing Chen, Muning Wen, Ying Wen, Fanglei Sun

VOS: Learning What You Don't Know by Virtual Outlier Synthesis

Xuefeng Du, Zhaoning Wang, Mu Cai, Yixuan Li

Critical Points in Quantum Generative Models

Eric Ricardo Anschuetz

A Relational Intervention Approach for Unsupervised Dynamics Generalization in Model-Based Reinforcement Learning

Jiaxian Guo, Mingming Gong, Dacheng Tao

Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling

Gianluigi Silvestri, Emily Fertig, Dave Moore, Luca Ambrogioni

Learning Prototype-oriented Set Representations for Meta-Learning

Dan dan Guo, Long Tian, Minghe Zhang, Mingyuan Zhou, Hongyuan Zha

On the Learning and Learnability of Quasimetrics

Tongzhou Wang, Phillip Isola

Fooling Explanations in Text Classifiers

Adam Ivankay, Ivan Girardi, Chiara Marchiori, Pascal Frossard

Fairness Guarantees under Demographic Shift

Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas

Spherical Message Passing for 3D Molecular Graphs

Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang

Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction

Eli Chien, Wei-Cheng Chang, Cho-jui Hsieh, Hsiang-Fu Yu, Jiong Zhang

Know Thyself: Transferable Visual Control Policies Through Robot-Awareness

Edward S. Hu, Kun Huang, Oleh Rybkin, Dinesh Jayaraman

Latent Image Animator: Learning to Animate Images via Latent Space Navigation

Yaohui Wang, Di Yang, francois bremond, Antitza Dantcheva

Task Affinity with Maximum Bipartite Matching in Few-Shot Learning

Cat Phuoc Le, Juncheng Dong, Mohammadreza Soltani, Vahid Tarokh

Crystal Diffusion Variational Autoencoder for Periodic Material Generation

Tian Xie, Xiang Fu, Octavian-Eugen Ganea, Regina Barzilay, Tommi S. Jaakkola

Certified Robustness for Deep Equilibrium Models via Interval Bound Propagation

Colin Wei, J Zico Kolter

Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS Benchmarks

Arber Zela, Julien Niklas Siems, Lucas Zimmer, Jovita Lukasik, Margret Keuper

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

Yulun Wu, Nicholas Choma, Andrew Deru Chen, Mikaela Cashman, Erica Teixeira Prates

MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer

Sachin Mehta, Mohammad Rastegari

Communication-Efficient Actor-Critic Methods for Homogeneous Markov Games

Dingyang Chen, Yile Li, Qi Zhang

How to Train Your MAML to Excel in Few-Shot Classification

Han-Jia Ye, Wei-Lun Chao

NASI: Label- and Data-agnostic Neural Architecture Search at Initialization

YAO SHU, Shaofeng Cai, Zhongxiang Dai, Beng Chin Ooi, Bryan Kian Hsiang Low

Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods

Wenqing Zheng, Edward W Huang, Nikhil Rao, Sumeet Katariya, Zhangyang Wang

Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage

Masatoshi Uehara, Wen Sun

Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning

Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause

Learning curves for continual learning in neural networks: Self-knowledge transfer and forgetting

Ryo Karakida, Shotaro Akaho

Synchromesh: Reliable Code Generation from Pre-trained Language Models

Gabriel Poesia, Alex Polozov, Vu Le, Ashish Tiwari, Gustavo Soares

You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks

Eli Chien, Chao Pan, Jianhao Peng, Olgica Milenkovic

GradSign: Model Performance Inference with Theoretical Insights

Zhihao Zhang, Zhihao Jia

Do Not Escape From the Manifold: Discovering the Local Coordinates on the Latent Space of GANs

Jaewoong Choi, Junho Lee, Changyeon Yoon, Jung Ho Park, Geonho Hwang

Creating Training Sets via Weak Indirect Supervision

Jieyu Zhang, Bohan Wang, Xiangchen Song, Yujing Wang, Yaming Yang

Automated Self-Supervised Learning for Graphs

Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah

Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions

Juncheng Dong, Simiao Ren, Yang Deng, Omar Khatib, Jordan Malof

Sound and Complete Neural Network Repair with Minimality and Locality Guarantees

Feisi Fu, Wenchao Li

Causal Contextual Bandits with Targeted Interventions

Chandrasekar Subramanian, Balaraman Ravindran

Learning Continuous Environment Fields via Implicit Functions

Xueting Li, Shalini De Mello, Xiaolong Wang, Ming-Hsuan Yang, Jan Kautz

Differentiable Gradient Sampling for Learning Implicit 3D Scene Reconstructions from a Single Image

Shizhan Zhu, Sayna Ebrahimi, Angjoo Kanazawa, Trevor Darrell

Disentanglement Analysis with Partial Information Decomposition

Seiya Tokui, Issei Sato

Exploring Memorization in Adversarial Training

Yinpeng Dong, Ke Xu, Xiao Yang, Tianyu Pang, Zhijie Deng

WeakM3D: Towards Weakly Supervised Monocular 3D Object Detection

Liang Peng, Senbo Yan, Boxi Wu, Zheng Yang, Xiaofei He

The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models

Cassidy Laidlaw, Anca Dragan

Learning Value Functions from Undirected State-only Experience

Matthew Chang, Arjun Gupta, Saurabh Gupta

Topological Graph Neural Networks

Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck

How to deal with missing data in supervised deep learning?

Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen

Transferable Adversarial Attack based on Integrated Gradients

Yi Huang, Adams Wai-Kin Kong

HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation

Boyan Li, Hongyao Tang, YAN ZHENG, Jianye Hao, Pengyi Li

FALCON: Fast Visual Concept Learning by Integrating Images, Linguistic descriptions, and Conceptual Relations

Lingjie Mei, Jiayuan Mao, Ziqi Wang, Chuang Gan, Joshua B. Tenenbaum