ICLR 2022

1,094 papers

Automatic Loss Function Search for Predict-Then-Optimize Problems with Strong Ranking Property

Boshi Wang, Jialin Yi, Hang Dong, Bo Qiao, Chuan Luo

Handling Distribution Shifts on Graphs: An Invariance Perspective

Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf

Distilling GANs with Style-Mixed Triplets for X2I Translation with Limited Data

yaxing wang, Joost van de Weijer, Lu Yu, Shangling Jui

Towards Better Understanding and Better Generalization of Low-shot Classification in Histology Images with Contrastive Learning

Jiawei Yang, Hanbo Chen, Jiangpeng Yan, Xiaoyu Chen, Jianhua Yao

Neural Variational Dropout Processes

Insu Jeon, Youngjin Park, Gunhee Kim

SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation

Cong Guo, Yuxian Qiu, Jingwen Leng, Xiaotian Gao, Chen Zhang

Fast Differentiable Matrix Square Root

Yue Song, Nicu Sebe, Wei Wang

Group equivariant neural posterior estimation

Maximilian Dax, Stephen R Green, Jonathan Gair, Michael Deistler, Bernhard Schölkopf

Trivial or Impossible --- dichotomous data difficulty masks model differences (on ImageNet and beyond)

Kristof Meding, Luca M. Schulze Buschoff, Robert Geirhos, Felix A. Wichmann

ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity

Ginger Delmas, Rafael S. Rezende, Gabriela Csurka, Diane Larlus

Deep Attentive Variational Inference

Ifigeneia Apostolopoulou, Ian Char, Elan Rosenfeld, Artur Dubrawski

What’s Wrong with Deep Learning in Tree Search for Combinatorial Optimization

Maximilian Böther, Otto Kißig, Martin Taraz, Sarel Cohen, Karen Seidel

Visual Correspondence Hallucination

Hugo Germain, Vincent Lepetit, Guillaume Bourmaud

Quadtree Attention for Vision Transformers

Shitao Tang, Jiahui Zhang, Siyu Zhu, Ping Tan

RegionViT: Regional-to-Local Attention for Vision Transformers

Chun-Fu Chen, Rameswar Panda, Quanfu Fan

FedPara: Low-rank Hadamard Product for Communication-Efficient Federated Learning

Nam Hyeon-Woo, Moon Ye-Bin, Tae-Hyun Oh

Understanding Dimensional Collapse in Contrastive Self-supervised Learning

Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian

R4D: Utilizing Reference Objects for Long-Range Distance Estimation

Yingwei Li, Tiffany Chen, Maya Kabkab, Ruichi Yu, Longlong Jing

Surrogate Gap Minimization Improves Sharpness-Aware Training

Juntang Zhuang, Boqing Gong, Liangzhe Yuan, Yin Cui, Hartwig Adam

Gradient Step Denoiser for convergent Plug-and-Play

Samuel Hurault, Arthur Leclaire, Nicolas Papadakis

Unsupervised Discovery of Object Radiance Fields

Hong-Xing Yu, Leonidas Guibas, Jiajun Wu

Wisdom of Committees: An Overlooked Approach To Faster and More Accurate Models

Xiaofang Wang, Dan Kondratyuk, Eric Christiansen, Kris M. Kitani, Yair Movshovitz-Attias

A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning

Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta

Declarative nets that are equilibrium models

Russell Tsuchida, Suk Yee Yong, Mohammad Ali Armin, Lars Petersson, Cheng Soon Ong

Anytime Dense Prediction with Confidence Adaptivity

Zhuang Liu, Zhiqiu Xu, Hung-Ju Wang, Trevor Darrell, Evan Shelhamer

Online Adversarial Attacks

Andjela Mladenovic, Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien

Uncertainty Modeling for Out-of-Distribution Generalization

Xiaotong Li, Yongxing Dai, Yixiao Ge, Jun Liu, Ying Shan

Learning Efficient Online 3D Bin Packing on Packing Configuration Trees

Hang Zhao, Yang Yu, Kai Xu

Rethinking Class-Prior Estimation for Positive-Unlabeled Learning

Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu

You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction

Osama Makansi, Julius von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Dominik Janzing

QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization

Xiuying Wei, Ruihao Gong, Yuhang Li, Xianglong Liu, Fengwei Yu

Dropout Q-Functions for Doubly Efficient Reinforcement Learning

Takuya Hiraoka, Takahisa Imagawa, Taisei Hashimoto, Takashi Onishi, Yoshimasa Tsuruoka

A generalization of the randomized singular value decomposition

Nicolas Boulle, Alex Townsend

Bregman Gradient Policy Optimization

Feihu Huang, Shangqian Gao, Heng Huang

Neural Relational Inference with Node-Specific Information

Ershad Banijamali

The Rich Get Richer: Disparate Impact of Semi-Supervised Learning

Zhaowei Zhu, Tianyi Luo, Yang Liu

Learning Temporally Causal Latent Processes from General Temporal Data

Weiran Yao, Yuewen Sun, Alex Ho, Changyin Sun, Kun Zhang

Learning Representation from Neural Fisher Kernel with Low-rank Approximation

Ruixiang ZHANG, Shuangfei Zhai, Etai Littwin, Joshua M. Susskind

Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

Ofir Press, Noah Smith, Mike Lewis

Vector-quantized Image Modeling with Improved VQGAN

Jiahui Yu, Xin Li, Jing Yu Koh, Han Zhang, Ruoming Pang

Learning to Annotate Part Segmentation with Gradient Matching

Yu Yang, Xiaotian Cheng, Hakan Bilen, Xiangyang Ji

Optimization inspired Multi-Branch Equilibrium Models

Mingjie Li, Yisen Wang, Xingyu Xie, Zhouchen Lin

Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations

Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu

Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference

Hyunseo Koh, Dahyun Kim, Jung-Woo Ha, Jonghyun Choi

AS-MLP: An Axial Shifted MLP Architecture for Vision

Dongze Lian, Zehao Yu, Xing Sun, Shenghua Gao

Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks

Tong Bu, Wei Fang, Jianhao Ding, Penglin Dai, Zhaofei Yu

Modular Lifelong Reinforcement Learning via Neural Composition

Jorge A Mendez, Harm Van Seijen, Eric Eaton

Learned Simulators for Turbulence

Kim Stachenfeld, Drummond Buschman Fielding, Dmitrii Kochkov, Miles Cranmer, Tobias Pfaff

Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation

Yan Zhang, David W Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek

Concurrent Adversarial Learning for Large-Batch Training

Yong Liu, Xiangning Chen, Minhao Cheng, Cho-jui Hsieh, Yang You

On the Convergence of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning

Che Wang, Shuhan Yuan, Kai Shao, Keith W. Ross

Discrete Representations Strengthen Vision Transformer Robustness

Chengzhi Mao, Lu Jiang, Mostafa Dehghani, Carl Vondrick, Rahul Sukthankar

In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications

Borja G. Leon, Murray Shanahan, Francesco Belardinelli

How Low Can We Go: Trading Memory for Error in Low-Precision Training

Chengrun Yang, Ziyang Wu, Jerry Chee, Christopher De Sa, Madeleine Udell

Differentially Private Fractional Frequency Moments Estimation with Polylogarithmic Space

Lun Wang, Iosif Pinelis, Dawn Song

Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs

Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Mysore Nagaraj, Praneeth Netrapalli

Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity

Byungseok Roh, JaeWoong Shin, Wuhyun Shin, Saehoon Kim

Stein Latent Optimization for Generative Adversarial Networks

Uiwon Hwang, Heeseung Kim, Dahuin Jung, Hyemi Jang, HyunGyu Lee

X-model: Improving Data Efficiency in Deep Learning with A Minimax Model

Ximei Wang, Xinyang Chen, Jianmin Wang, Mingsheng Long

Constructing Orthogonal Convolutions in an Explicit Manner

Tan Yu, Jun Li, Yunfeng Cai, Ping Li

Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels

Wentao Zhang, Yexin Wang, Zhenbang You, Meng Cao, Ping Huang

Multimeasurement Generative Models

Saeed Saremi, Rupesh Kumar Srivastava

Contrastive Clustering to Mine Pseudo Parallel Data for Unsupervised Translation

Xuan-Phi Nguyen, Hongyu Gong, Yun Tang, Changhan Wang, Philipp Koehn

An Unconstrained Layer-Peeled Perspective on Neural Collapse

Wenlong Ji, Yiping Lu, Yiliang Zhang, Zhun Deng, Weijie J Su

Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks

Andrea Cini, Ivan Marisca, Cesare Alippi

Pareto Policy Pool for Model-based Offline Reinforcement Learning

Yijun Yang, Jing Jiang, Tianyi Zhou, Jie Ma, Yuhui Shi

Generative Principal Component Analysis

Zhaoqiang Liu, Jiulong Liu, Subhroshekhar Ghosh, JUN HAN, Jonathan Scarlett

Bootstrapping Semantic Segmentation with Regional Contrast

Shikun Liu, Shuaifeng Zhi, Edward Johns, Andrew Davison

Signing the Supermask: Keep, Hide, Invert

Nils Koster, Oliver Grothe, Achim Rettinger

Pseudo-Labeled Auto-Curriculum Learning for Semi-Supervised Keypoint Localization

Can Wang, Sheng Jin, Yingda Guan, Wentao Liu, Chen Qian

Efficient Neural Causal Discovery without Acyclicity Constraints

Phillip Lippe, Taco Cohen, Efstratios Gavves

On the Certified Robustness for Ensemble Models and Beyond

Zhuolin Yang, Linyi Li, Xiaojun Xu, Bhavya Kailkhura, Tao Xie

DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR

Shilong Liu, Feng Li, Hao Zhang, Xiao Yang, Xianbiao Qi

Reverse Engineering of Imperceptible Adversarial Image Perturbations

Yifan Gong, Yuguang Yao, Yize Li, Yimeng Zhang, Xiaoming Liu

Learning to Complete Code with Sketches

Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt

Backdoor Defense via Decoupling the Training Process

Kunzhe Huang, Yiming Li, Baoyuan Wu, Zhan Qin, Kui Ren

Few-Shot Backdoor Attacks on Visual Object Tracking

Yiming Li, Haoxiang Zhong, Xingjun Ma, Yong Jiang, Shu-Tao Xia

Online Facility Location with Predictions

Shaofeng H.-C. Jiang, Erzhi Liu, You Lyu, Zhihao Gavin Tang, Yubo Zhang

Learning Super-Features for Image Retrieval

Philippe Weinzaepfel, Thomas Lucas, Diane Larlus, Yannis Kalantidis

Should We Be Pre-training? An Argument for End-task Aware Training as an Alternative

Lucio M. Dery, Paul Michel, Ameet Talwalkar, Graham Neubig

Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond

Jonathan Godwin, Michael Schaarschmidt, Alexander L Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova

Is High Variance Unavoidable in RL? A Case Study in Continuous Control

Johan Bjorck, Carla P Gomes, Kilian Q Weinberger

Do We Need Anisotropic Graph Neural Networks?

Shyam A. Tailor, Felix Opolka, Pietro Lió, Nicholas Donald Lane

Accelerated Policy Learning with Parallel Differentiable Simulation

Jie Xu, Viktor Makoviychuk, Yashraj Narang, Fabio Ramos, Wojciech Matusik

Image BERT Pre-training with Online Tokenizer

Jinghao Zhou, CHEN WEI, Huiyu Wang, Wei Shen, Cihang Xie

Language-driven Semantic Segmentation

Boyi Li, Kilian Q Weinberger, Serge Belongie, Vladlen Koltun, Rene Ranftl

Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception

Yurong You, Katie Z Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao

On the role of population heterogeneity in emergent communication

Mathieu Rita, Florian Strub, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux

Privacy Implications of Shuffling

Casey Meehan, Amrita Roy Chowdhury, Kamalika Chaudhuri, Somesh Jha

Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps

Nico Courts, Henry Kvinge

SimVLM: Simple Visual Language Model Pretraining with Weak Supervision

Zirui Wang, Jiahui Yu, Adams Wei Yu, Zihang Dai, Yulia Tsvetkov

Safe Neurosymbolic Learning with Differentiable Symbolic Execution

Chenxi Yang, Swarat Chaudhuri

Efficient and Differentiable Conformal Prediction with General Function Classes

Yu Bai, Song Mei, Huan Wang, Yingbo Zhou, Caiming Xiong

FP-DETR: Detection Transformer Advanced by Fully Pre-training

Wen Wang, Yang Cao, Jing Zhang, Dacheng Tao

MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts

Weixin Liang, James Zou

Associated Learning: an Alternative to End-to-End Backpropagation that Works on CNN, RNN, and Transformer

Dennis Y.H. Wu, Dinan Lin, Vincent Chen, Hung-Hsuan Chen

Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization

Tolga Ergen, Arda Sahiner, Batu Ozturkler, John M. Pauly, Morteza Mardani

New Insights on Reducing Abrupt Representation Change in Online Continual Learning

Lucas Caccia, Rahaf Aljundi, Nader Asadi, Tinne Tuytelaars, Joelle Pineau

Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework

Xu Ma, Can Qin, Haoxuan You, Haoxi Ran, Yun Fu

Decoupled Adaptation for Cross-Domain Object Detection

Junguang Jiang, Baixu Chen, Jianmin Wang, Mingsheng Long