NeurIPS 2021

2,334 papers

Multi-View Representation Learning via Total Correlation Objective

HyeongJoo Hwang, Geon-hyeong Kim, Seunghoon Hong, Kee-eung Kim

Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation

Robert A Vandermeulen, Antoine Ledent

Explaining heterogeneity in medial entorhinal cortex with task-driven neural networks

Aran Nayebi, Alexander Attinger, Malcolm Campbell, Kiah Hardcastle, Isabel Low

Explaining Latent Representations with a Corpus of Examples

Jonathan Crabbe, Zhaozhi Qian, Fergus Imrie, Mihaela van der Schaar

Delayed Propagation Transformer: A Universal Computation Engine towards Practical Control in Cyber-Physical Systems

Wenqing Zheng, Qiangqiang Guo, Hao Yang, Peihao Wang, Zhangyang Wang

Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning

Ali Taghibakhshi, Scott MacLachlan, Luke Olson, Matthew West

Do Vision Transformers See Like Convolutional Neural Networks?

Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy

Residual Relaxation for Multi-view Representation Learning

Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang

Fairness via Representation Neutralization

Mengnan Du, Subhabrata Mukherjee, Guanchu Wang, Ruixiang Tang, Ahmed Awadallah

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez

On The Structure of Parametric Tournaments with Application to Ranking from Pairwise Comparisons

Vishnu Veerathu, Arun Rajkumar

Fast Federated Learning in the Presence of Arbitrary Device Unavailability

Xinran Gu, Kaixuan Huang, Jingzhao Zhang, Longbo Huang

A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning

Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert

Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks

Hassan Dbouk, Naresh Shanbhag

ATISS: Autoregressive Transformers for Indoor Scene Synthesis

Despoina Paschalidou, Amlan Kar, Maria Shugrina, Karsten Kreis, Andreas Geiger

A Geometric Structure of Acceleration and Its Role in Making Gradients Small Fast

Jongmin Lee, Chanwoo Park, Ernest Ryu

Learning in two-player zero-sum partially observable Markov games with perfect recall

Tadashi Kozuno, Pierre Menard, Rémi Munos, Michal Valko

Contrastive Learning for Neural Topic Model

Thong Nguyen, Anh Tuan Luu

Not All Images are Worth 16x16 Words: Dynamic Transformers for Efficient Image Recognition

Yulin Wang, Rui Huang, Shiji Song, Zeyi Huang, Gao Huang

Joint Semantic Mining for Weakly Supervised RGB-D Salient Object Detection

Jingjing Li, Wei Ji, Qi Bi, Cheng Yan, Miao Zhang

Batch Active Learning at Scale

Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan

Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data

Gongfan Fang, Yifan Bao, Jie Song, Xinchao Wang, Donglin Xie

Generalized Proximal Policy Optimization with Sample Reuse

James Queeney, Yannis Paschalidis, Christos G Cassandras

Fairness in Ranking under Uncertainty

Ashudeep Singh, David Kempe, Thorsten Joachims

An Uncertainty Principle is a Price of Privacy-Preserving Microdata

John Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson Garfinkel, Daniel Kifer

Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems

Andreas Schlaginhaufen, Philippe Wenk, Andreas Krause, Florian Dorfler

Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees

Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui

Detecting Moments and Highlights in Videos via Natural Language Queries

Jie Lei, Mohit Bansal, Tamara L. Berg, Tamara L Berg

Intriguing Properties of Contrastive Losses

Ting Chen, Calvin Luo, Lala Li

Towards Efficient and Effective Adversarial Training

Gaurang Sriramanan, Sravanti Addepalli, Arya Baburaj, Venkatesh Babu R

Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence

Deng-Bao Wang, Lei Feng, Min-ling Zhang

Sparse Spiking Gradient Descent

Nicolas Perez-Nieves, Dan Goodman

Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation

Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang

Meta-Learning Sparse Implicit Neural Representations

Jaeho Lee, Jihoon Tack, Namhoon Lee, Jinwoo Shin

Coarse-to-fine Animal Pose and Shape Estimation

Chen Li, Gim Hee Lee

Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems

Ruihan Wu, Chuan Guo, Awni Hannun, Laurens van der Maaten

How Well do Feature Visualizations Support Causal Understanding of CNN Activations?

Roland S. Zimmermann, Judy Borowski, Robert Geirhos, Matthias Bethge, Thomas Wallis

Impression learning: Online representation learning with synaptic plasticity

Colin Bredenberg, Benjamin Lyo, Eero P. Simoncelli, Cristina Savin

Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism

Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart J. Russell

Foundations of Symbolic Languages for Model Interpretability

Marcelo Arenas, Daniel Báez, Pablo Barceló, Jorge Pérez, Bernardo Subercaseaux

Hyperparameter Tuning is All You Need for LISTA

Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin

Overlapping Spaces for Compact Graph Representations

Kirill Shevkunov, Liudmila Prokhorenkova

Sequential Algorithms for Testing Closeness of Distributions

Aadil Oufkir, Omar Fawzi, Nicolas Flammarion, Aurélien Garivier

Coresets for Classification – Simplified and Strengthened

Tung Mai, Cameron Musco, Anup Rao

Numerical Composition of Differential Privacy

Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz

Pure Exploration in Kernel and Neural Bandits

Yinglun Zhu, Dongruo Zhou, Ruoxi Jiang, Quanquan Gu, Rebecca Willett

Learning to Generate Visual Questions with Noisy Supervision

Shen Kai, Lingfei Wu, Siliang Tang, Yueting Zhuang, Zhen He

DeepGEM: Generalized Expectation-Maximization for Blind Inversion

Angela Gao, Jorge Castellanos, Yisong Yue, Zachary Ross, Katherine Bouman

Submodular + Concave

Siddharth Mitra, Moran Feldman, Amin Karbasi

Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models

Phil Chen, Mikhal Itkina, Ransalu Senanayake, Mykel J Kochenderfer

Hierarchical Skills for Efficient Exploration

Jonas Gehring, Gabriel Synnaeve, Andreas Krause, Nicolas Usunier

Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification

Ben Eysenbach, Sergey Levine, Ruslan Salakhutdinov

What’s a good imputation to predict with missing values?

Marine Le Morvan, Julie Josse, Erwan Scornet, Gael Varoquaux

Universal Rate-Distortion-Perception Representations for Lossy Compression

George Zhang, Jingjing Qian, Jun Chen, Ashish Khisti

Conservative Data Sharing for Multi-Task Offline Reinforcement Learning

Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine

Learning to dehaze with polarization

Chu Zhou, Minggui Teng, Yufei Han, Chao Xu, Boxin Shi

Dual Parameterization of Sparse Variational Gaussian Processes

Vincent ADAM, Paul Chang, Mohammad Emtiyaz Khan, Arno Solin

Littlestone Classes are Privately Online Learnable

Noah Golowich, Roi Livni

Exploring Cross-Video and Cross-Modality Signals for Weakly-Supervised Audio-Visual Video Parsing

Yan-Bo Lin, Hung-Yu Tseng, Hsin-Ying Lee, Yen-yu Lin, Ming-Hsuan Yang

Entropic Desired Dynamics for Intrinsic Control

Steven Hansen, Guillaume Desjardins, Kate Baumli, David Warde-Farley, Nicolas Heess

An Improved Analysis of Gradient Tracking for Decentralized Machine Learning

Anastasiia Koloskova, Tao LIN, Sebastian U Stich

Decrypting Cryptic Crosswords: Semantically Complex Wordplay Puzzles as a Target for NLP

Josh Rozner, Christopher Potts, Kyle Mahowald

Faster proximal algorithms for matrix optimization using Jacobi-based eigenvalue methods

Hamza Fawzi, Harry Goulbourne

Shifted Chunk Transformer for Spatio-Temporal Representational Learning

Xuefan Zha, Wentao Zhu, Lv Xun, Sen Yang, Ji Liu

Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression

Zhaozhi Qian, William Zame, Lucas Fleuren, Paul Elbers, Mihaela van der Schaar

One Explanation is Not Enough: Structured Attention Graphs for Image Classification

Vivswan Shitole, Fuxin Li, Minsuk Kahng, Prasad Tadepalli, Alan Fern

Online Adaptation to Label Distribution Shift

Ruihan Wu, Chuan Guo, Yi Su, Kilian Q. Weinberger

Tensor decompositions of higher-order correlations by nonlinear Hebbian plasticity

Gabriel Ocker, Michael Buice

Bootstrap Your Object Detector via Mixed Training

Mengde Xu, Zheng Zhang, Fangyun Wei, Yutong Lin, Yue Cao

Deep Conditional Gaussian Mixture Model for Constrained Clustering

Laura Manduchi, Kieran Chin-Cheong, Holger Michel, Sven Wellmann, Julia Vogt

Score-based Generative Modeling in Latent Space

Arash Vahdat, Karsten Kreis, Jan Kautz

Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators

Qitian Wu, RUI GAO, Hongyuan Zha

Continuous Doubly Constrained Batch Reinforcement Learning

Rasool Fakoor, Jonas W Mueller, Kavosh Asadi, Pratik Chaudhari, Alexander J Smola

Subquadratic Overparameterization for Shallow Neural Networks

ChaeHwan Song, Ali Ramezani-Kebrya, Thomas Pethick, Armin eftekhari, Volkan Cevher

Optimal prediction of Markov chains with and without spectral gap

Yanjun Han, Soham Jana, Yihong Wu

Federated Reconstruction: Partially Local Federated Learning

Karan Singhal, Hakim Sidahmed, Zachary Garrett, Shanshan Wu, John Rush

Making the most of your day: online learning for optimal allocation of time

Etienne Boursier, Tristan Garrec, Vianney Perchet, Marco Scarsini

Controlling Neural Networks with Rule Representations

Sungyong Seo, Sercan Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn

Counterbalancing Learning and Strategic Incentives in Allocation Markets

Jamie Kang, Faidra Monachou, Moran Koren, Itai Ashlagi

Lifelong Domain Adaptation via Consolidated Internal Distribution

Mohammad Rostami

Linear-Time Probabilistic Solution of Boundary Value Problems

Nicholas Krämer, Philipp Hennig

Oracle-Efficient Regret Minimization in Factored MDPs with Unknown Structure

Aviv Rosenberg, Yishay Mansour

Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications

Leonard Berrada, Sumanth Dathathri, Krishnamurthy Dvijotham, Robert Stanforth, Rudy R Bunel

Differentiable Synthesis of Program Architectures

Guofeng Cui, He Zhu

Learning interaction rules from multi-animal trajectories via augmented behavioral models

Keisuke Fujii, Naoya Takeishi, Kazushi Tsutsui, Emyo Fujioka, Nozomi Nishiumi

Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer

Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Le Zhang

Multi-task Learning of Order-Consistent Causal Graphs

Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song

Selective Sampling for Online Best-arm Identification

Romain Camilleri, Zhihan Xiong, Maryam Fazel, Lalit Jain, Kevin G. Jamieson

True Few-Shot Learning with Language Models

Ethan Perez, Douwe Kiela, Kyunghyun Cho

Robust Visual Reasoning via Language Guided Neural Module Networks

Arjun Akula, Varun Jampani, Soravit Changpinyo, Song-chun Zhu

Dynamic Normalization and Relay for Video Action Recognition

Dongqi Cai, Anbang Yao, Yurong Chen

Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling

Greg Ver Steeg, Aram Galstyan

Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces

Kirill Struminsky, Artyom Gadetsky, Denis Rakitin, Danil Karpushkin, Dmitry P Vetrov

Dynamic Inference with Neural Interpreters

Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio

Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification

Youngseog Chung, Willie Neiswanger, Ian Char, Jeff G. Schneider

Quantifying and Improving Transferability in Domain Generalization

Guojun Zhang, Han Zhao, Yaoliang Yu, Pascal Poupart

What Makes Multi-Modal Learning Better than Single (Provably)

Yu Huang, Chenzhuang Du, Zihui Xue, Xuanyao Chen, Hang Zhao

Lower and Upper Bounds on the Pseudo-Dimension of Tensor Network Models

Behnoush Khavari, Guillaume Rabusseau

SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning

Sungmin Cha, beomyoung kim, YoungJoon Yoo, Taesup Moon

Diversity Enhanced Active Learning with Strictly Proper Scoring Rules

Wei Tan, Lan Du, Wray Buntine