NeurIPS 2021

2,334 papers

A Regression Approach to Learning-Augmented Online Algorithms

Keerti Anand, Rong Ge, Amit Kumar, Debmalya Panigrahi

Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection

NA DONG, Yongqiang Zhang, Mingli Ding, Gim Hee Lee

Scalable Rule-Based Representation Learning for Interpretable Classification

Zhuo Wang, Wei Zhang, Ning Liu, Jianyong Wang

Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data

Andrew Jesson, Panagiotis Tigas, Joost van Amersfoort, Andreas Kirsch, Uri Shalit

Unlabeled Principal Component Analysis

Yunzhen Yao, Liangzu Peng, Manolis Tsakiris

Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning

Vivien Cabannes, Loucas Pillaud-Vivien, Francis R. Bach, Alessandro Rudi

Meta-Learning for Relative Density-Ratio Estimation

Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

InfoGCL: Information-Aware Graph Contrastive Learning

Dongkuan Xu, Wei Cheng, Dongsheng Luo, Haifeng Chen, Xiang Zhang

Error Compensated Distributed SGD Can Be Accelerated

Xun Qian, Peter Richtarik, Tong Zhang

Early Convolutions Help Transformers See Better

Tete Xiao, Mannat Singh, Eric Mintun, Trevor Darrell, Piotr Dollár

MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction

Hao Xue, Flora Salim, Yongli Ren, Nuria Oliver

Local plasticity rules can learn deep representations using self-supervised contrastive predictions

Bernd Illing, Jean Ventura, Guillaume Bellec, Wulfram Gerstner

Coresets for Decision Trees of Signals

Ibrahim Jubran, Ernesto Evgeniy Sanches Shayda, Ilan I Newman, Dan Feldman

Adversarial Examples Make Strong Poisons

Liam Fowl, Micah Goldblum, Ping-yeh Chiang, Jonas Geiping, Wojciech Czaja

FedDR – Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization

Quoc Tran Dinh, Nhan H Pham, Dzung Phan, Lam Nguyen

Model-Based Episodic Memory Induces Dynamic Hybrid Controls

Hung Le, Thommen Karimpanal George, Majid Abdolshah, Truyen Tran, Svetha Venkatesh

Continual Learning via Local Module Composition

Oleksiy Ostapenko, Pau Rodriguez, Massimo Caccia, Laurent Charlin

Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels

Erik Englesson, Hossein Azizpour

A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum

Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang

Structural Credit Assignment in Neural Networks using Reinforcement Learning

Dhawal Gupta, Gabor Mihucz, Matthew Schlegel, James Kostas, Philip S. Thomas

On the Generative Utility of Cyclic Conditionals

Chang Liu, Haoyue Tang, Tao Qin, Jintao Wang, Tie-yan Liu

Rectangular Flows for Manifold Learning

Anthony L Caterini, Gabriel Loaiza-Ganem, Geoff Pleiss, John P. Cunningham

Are My Deep Learning Systems Fair? An Empirical Study of Fixed-Seed Training

Shangshu Qian, Viet Hung Pham, Thibaud Lutellier, Zeou Hu, Jungwon Kim

Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory

Zeru Zhang, Jiayin Jin, Zijie Zhang, Yang Zhou, Xin Zhao

Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks

Maksym Yatsura, Jan Metzen, Matthias Hein

Action-guided 3D Human Motion Prediction

Jiangxin Sun, Zihang Lin, Xintong Han, Jian-Fang Hu, Jia Xu

SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness

Jongheon Jeong, Sejun Park, Minkyu Kim, Heung-Chang Lee, Do-Guk Kim

Streaming Linear System Identification with Reverse Experience Replay

Suhas Kowshik, Dheeraj Nagaraj, Prateek Jain, Praneeth Netrapalli

Counterfactual Explanations in Sequential Decision Making Under Uncertainty

Stratis Tsirtsis, Abir De, Manuel Rodriguez

MICo: Improved representations via sampling-based state similarity for Markov decision processes

Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden, Mark Rowland

Provable Representation Learning for Imitation with Contrastive Fourier Features

Ofir Nachum, Mengjiao Yang

Dynamic Trace Estimation

Prathamesh Dharangutte, Christopher Musco

Learning Large Neighborhood Search Policy for Integer Programming

Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang

Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize

Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman

Optimal Algorithms for Stochastic Contextual Preference Bandits

Aadirupa Saha

Residual Pathway Priors for Soft Equivariance Constraints

Marc Finzi, Gregory Benton, Andrew G Wilson

Scalable and Stable Surrogates for Flexible Classifiers with Fairness Constraints

Henry C Bendekgey, Erik B. Sudderth

Focal Attention for Long-Range Interactions in Vision Transformers

Jianwei Yang, Chunyuan Li, Pengchuan Zhang, Xiyang Dai, Bin Xiao

Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning

Ligeng Zhu, Hongzhou Lin, Yao Lu, Yujun Lin, Song Han

Batched Thompson Sampling

Cem Kalkanli, Ayfer Ozgur

Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects

Denys Rozumnyi, Martin R. Oswald, Vittorio Ferrari, Marc Pollefeys

Shared Independent Component Analysis for Multi-Subject Neuroimaging

Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo Hyvärinen

Deep Explicit Duration Switching Models for Time Series

Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Turkmen, Harold Soh

Data Augmentation Can Improve Robustness

Sylvestre-Alvise Rebuffi, Sven Gowal, Dan Andrei Calian, Florian Stimberg, Olivia Wiles

Autobahn: Automorphism-based Graph Neural Nets

Erik Thiede, Wenda Zhou, Risi Kondor

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification

Shiqi Wang, Huan Zhang, Kaidi Xu, Xue Lin, Suman Jana

Gradient Inversion with Generative Image Prior

Jinwoo Jeon, jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok

Topology-Imbalance Learning for Semi-Supervised Node Classification

Deli Chen, Yankai Lin, Guangxiang Zhao, Xuancheng Ren, Peng Li

Near-Optimal Lower Bounds For Convex Optimization For All Orders of Smoothness

Ankit Garg, Robin Kothari, Praneeth Netrapalli, Suhail Sherif

Discovery of Options via Meta-Learned Subgoals

Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh

Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning

Yifan Zhang, Bryan Hooi, Dapeng Hu, Jian Liang, Jiashi Feng

NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild

Jason Zhang, Gengshan Yang, Shubham Tulsiani, Deva Ramanan

A Geometric Analysis of Neural Collapse with Unconstrained Features

Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You

Adjusting for Autocorrelated Errors in Neural Networks for Time Series

Fan-Keng Sun, Chris Lang, Duane Boning

Shaping embodied agent behavior with activity-context priors from egocentric video

Tushar Nagarajan, Kristen Grauman

Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models

Lenart Treven, Philippe Wenk, Florian Dorfler, Andreas Krause

Soft Calibration Objectives for Neural Networks

Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens

Robust Generalization despite Distribution Shift via Minimum Discriminating Information

Tobias Sutter, Andreas Krause, Daniel Huhn

Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections

NABARUN DEB, Promit Ghosal, Bodhisattva Sen

Differentially Private Model Personalization

Prateek Jain, John Rush, Adam Smith, Shuang Song, Abhradeep Guha Thakurta

BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation

Mingcong Liu, Qiang Li, Zekui Qin, Guoxin Zhang, Pengfei Wan

Activation Sharing with Asymmetric Paths Solves Weight Transport Problem without Bidirectional Connection

Sunghyeon Woo, Jeongwoo Park, Jiwoo Hong, Dongsuk Jeon

Robust Allocations with Diversity Constraints

Zeyu Shen, Lodewijk Gelauff, Ashish Goel, Aleksandra Korolova, Kamesh Munagala

Program Synthesis Guided Reinforcement Learning for Partially Observed Environments

Yichen Yang, Jeevana Priya Inala, Osbert Bastani, Yewen Pu, Armando Solar-Lezama

Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models

Runzhe Wan, Lin Ge, Rui Song

Corruption Robust Active Learning

Yifang Chen, Simon S Du, Kevin G. Jamieson

Automatic and Harmless Regularization with Constrained and Lexicographic Optimization: A Dynamic Barrier Approach

Chengyue Gong, Xingchao Liu, Qiang Liu

PCA Initialization for Approximate Message Passing in Rotationally Invariant Models

Marco Mondelli, Ramji Venkataramanan

On the Cryptographic Hardness of Learning Single Periodic Neurons

Min Jae Song, Ilias Zadik, Joan Bruna

Clustering Effect of Adversarial Robust Models

Yang Bai, Xin Yan, Yong Jiang, Shu-Tao Xia, Yisen Wang

Neural Architecture Dilation for Adversarial Robustness

Yanxi Li, Zhaohui Yang, Yunhe Wang, Chang Xu

On the Role of Optimization in Double Descent: A Least Squares Study

Ilja Kuzborskij, Csaba Szepesvári, Omar Rivasplata, Amal Rannen-Triki, Razvan Pascanu

Federated-EM with heterogeneity mitigation and variance reduction

Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Geneviève Robin

Learning Distilled Collaboration Graph for Multi-Agent Perception

Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng

ELLA: Exploration through Learned Language Abstraction

Suvir Mirchandani, Siddharth Karamcheti, Dorsa Sadigh

SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression

Steve Yadlowsky, Taedong Yun, Cory Y McLean, Alexander D'Amour

Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning

Nan Ding, Xi Chen, Tomer Levinboim, Sebastian Goodman, Radu Soricut

CorticalFlow: A Diffeomorphic Mesh Transformer Network for Cortical Surface Reconstruction

Leo Lebrat, Rodrigo Santa Cruz, Frederic de Gournay, Darren Fu, Pierrick Bourgeat

Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction

Zhaocheng Zhu, Zuobai Zhang, Louis-Pascal Xhonneux, Jian Tang

Square Root Principal Component Pursuit: Tuning-Free Noisy Robust Matrix Recovery

Junhui Zhang, Jingkai Yan, John Wright

FMMformer: Efficient and Flexible Transformer via Decomposed Near-field and Far-field Attention

Tan Nguyen, Vai Suliafu, Stanley Osher, Long Chen, Bao Wang

Parameter Prediction for Unseen Deep Architectures

Boris Knyazev, Michal Drozdzal, Graham W. Taylor, Adriana Romero Soriano

Offline Reinforcement Learning with Reverse Model-based Imagination

Jianhao Wang, Wenzhe Li, Haozhe Jiang, Guangxiang Zhu, Siyuan Li

Learning with Noisy Correspondence for Cross-modal Matching

Zhenyu Huang, Guocheng Niu, Xiao Liu, Wenbiao Ding, Xinyan Xiao

Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation

Shiqi Yang, yaxing wang, Joost van de Weijer, Luis Herranz, Shangling Jui

Targeted Neural Dynamical Modeling

Cole Hurwitz, Akash Srivastava, Kai Xu, Justin Jude, Matthew Perich

Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks

Melih Barsbey, Milad Sefidgaran, Murat A Erdogdu, Gaël RICHARD, Umut Simsekli

Mind the Gap: Assessing Temporal Generalization in Neural Language Models

Angeliki Lazaridou, Adhi Kuncoro, Elena Gribovskaya, Devang Agrawal, Adam Liska

DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning

Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen

DRONE: Data-aware Low-rank Compression for Large NLP Models

Patrick Chen, Hsiang-Fu Yu, Cho-jui Hsieh, Inderjit S Dhillon, Inderjit S. Dhillon

Deep Reinforcement Learning at the Edge of the Statistical Precipice

Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc Bellemare

Language models enable zero-shot prediction of the effects of mutations on protein function

Joshua Meier, Roshan Rao, Robert Verkuil, Jason Liu, Tom Sercu

Stabilizing Dynamical Systems via Policy Gradient Methods

Juan Perdomo, Jack Umenberger, Max Simchowitz

How Does it Sound?

Kun Su, Xiulong Liu, Eli Shlizerman

Clockwork Variational Autoencoders

Vaibhav Saxena, Jimmy Ba, Danijar Hafner

Iterative Teacher-Aware Learning

Luyao Yuan, Dongruo Zhou, Junhong Shen, Jingdong Gao, Jeffrey L Chen

Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity

Scott Pesme, Loucas Pillaud-Vivien, Nicolas Flammarion

Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time

Ferran Alet, Maria Bauza, Kenji Kawaguchi, Nurullah Giray Kuru, Tomás Lozano-Pérez

Gradient-based Editing of Memory Examples for Online Task-free Continual Learning

Xisen Jin, Arka Sadhu, Junyi Du, Xiang Ren

Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning

Antonious Girgis, Deepesh Data, Suhas Diggavi