NeurIPS 2021

2,334 papers

Self-Supervised Bug Detection and Repair

Miltiadis Allamanis, Henry Jackson-Flux, Marc Brockschmidt

Online Learning and Control of Complex Dynamical Systems from Sensory Input

Oumayma Bounou, Jean Ponce, Justin Carpentier

Robustness between the worst and average case

Leslie Rice, Anna Bair, Huan Zhang, J. Zico Kolter

Unsupervised Speech Recognition

Alexei Baevski, Wei-Ning Hsu, Alexis CONNEAU, Michael Auli

Robust Predictable Control

Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine

A generative nonparametric Bayesian model for whole genomes

Alan Amin, Eli N Weinstein, Debora Marks

Automated Dynamic Mechanism Design

Hanrui Zhang, Vincent Conitzer

Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy to Game

Alexander Reisach, Christof Seiler, Sebastian Weichwald

Dueling Bandits with Adversarial Sleeping

Aadirupa Saha, Pierre Gaillard

Dynamic COVID risk assessment accounting for community virus exposure from a spatial-temporal transmission model

Yuan Chen, Wenbo Fei, Qinxia Wang, Donglin Zeng, Yuanjia Wang

You Never Cluster Alone

Yuming Shen, Ziyi Shen, Menghan Wang, Jie Qin, Philip Torr

On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources

Trung Phung, Trung Le, Tung-Long Vuong, Toan Tran, Anh Tran

Faster Algorithms and Constant Lower Bounds for the Worst-Case Expected Error

Jonah Brown-Cohen

Permuton-induced Chinese Restaurant Process

Masahiro Nakano, Yasuhiro Fujiwara, Akisato Kimura, Takeshi Yamada, Naonori Ueda

Local Hyper-Flow Diffusion

Kimon Fountoulakis, Pan Li, Shenghao Yang

Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval

Omar Khattab, Christopher Potts, Matei Zaharia

DNN-based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel

Benjamin Dupuis, Arthur Jacot

Identifiable Generative models for Missing Not at Random Data Imputation

Chao Ma, Cheng Zhang

Improving Anytime Prediction with Parallel Cascaded Networks and a Temporal-Difference Loss

Michael Iuzzolino, Michael Mozer, Samy Bengio

Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration

Yu Wang, Jingyang Lin, Jingjing Zou, Yingwei Pan, Ting Yao

Near-Optimal No-Regret Learning in General Games

Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich

Stochastic Multi-Armed Bandits with Control Variates

Arun Verma, Manjesh Kumar Hanawal

Online and Offline Reinforcement Learning by Planning with a Learned Model

Julian Schrittwieser, Thomas Hubert, Amol Mandhane, Mohammadamin Barekatain, Ioannis Antonoglou

A Unified View of cGANs with and without Classifiers

Si-An Chen, Chun-Liang Li, Hsuan-tien Lin

Differentially Private Empirical Risk Minimization under the Fairness Lens

Cuong Tran, My Dinh, Ferdinando Fioretto

A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning

Weishi Shi, Dayou Yu, Qi Yu

DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales

Brandon Jacques, Zoran Tiganj, Marc Howard, Per B Sederberg

Instance-Conditioned GAN

Arantxa Casanova, Marlene Careil, Jakob J. Verbeek, Michal Drozdzal, Adriana Romero Soriano

Efficiently Identifying Task Groupings for Multi-Task Learning

Chris Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil

A Non-commutative Extension of Lee-Seung's Algorithm for Positive Semidefinite Factorizations

Yong Sheng Soh, Antonios Varvitsiotis

Universal Off-Policy Evaluation

Yash Chandak, Scott Niekum, Bruno da Silva, Erik Learned-Miller, Emma Brunskill

Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks

Sandesh Kamath, Amit Deshpande, Subrahmanyam Kambhampati Venkata, Vineeth N Balasubramanian

Label Noise SGD Provably Prefers Flat Global Minimizers

Alex Damian, Tengyu Ma, Jason Lee

AC-GC: Lossy Activation Compression with Guaranteed Convergence

R David Evans, Tor Aamodt

SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs

Ayush Sekhari, Karthik Sridharan, Satyen Kale

Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation

Jungbeom Lee, Jooyoung Choi, Jisoo Mok, Sungroh Yoon

Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning

Tengyang Xie, Nan Jiang, Huan Wang, Caiming Xiong, Yu Bai

Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation

Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio

General Low-rank Matrix Optimization: Geometric Analysis and Sharper Bounds

Haixiang Zhang, Yingjie Bi, Javad Lavaei

Robust Contrastive Learning Using Negative Samples with Diminished Semantics

Songwei Ge, Shlok Mishra, Chun-Liang Li, Haohan Wang, David Jacobs

Unsupervised Object-Based Transition Models For 3D Partially Observable Environments

Antonia Creswell, Rishabh Kabra, Chris Burgess, Murray Shanahan

Gauge Equivariant Transformer

Lingshen He, Yiming Dong, Yisen Wang, Dacheng Tao, Zhouchen Lin

Dynamic Resolution Network

Mingjian Zhu, Kai Han, Enhua Wu, Qiulin Zhang, Ying Nie

Online Market Equilibrium with Application to Fair Division

Yuan Gao, Alex Peysakhovich, Christian Kroer

Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond

Pan Zhou, Hanshu Yan, Xiaotong Yuan, Jiashi Feng, Shuicheng Yan

An analysis of Ermakov-Zolotukhin quadrature using kernels

Ayoub Belhadji

BARTScore: Evaluating Generated Text as Text Generation

Weizhe Yuan, Graham Neubig, Pengfei Liu

Improved Regularization and Robustness for Fine-tuning in Neural Networks

Dongyue Li, Hongyang Zhang

Localization with Sampling-Argmax

Jiefeng Li, Tong Chen, Ruiqi Shi, Yujing Lou, Yong-Lu Li

Improving Generalization in Meta-RL with Imaginary Tasks from Latent Dynamics Mixture

Suyoung Lee, Sae-Young Chung

Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies

Tim Seyde, Igor Gilitschenski, Wilko Schwarting, Bartolomeo Stellato, Martin Riedmiller

UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis

Zhu Zhang, Jianxin Ma, Chang Zhou, Rui Men, Zhikang Li

Improved Guarantees for Offline Stochastic Matching via new Ordered Contention Resolution Schemes

Brian Brubach, Nathaniel Grammel, Will Ma, Aravind Srinivasan

NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction

Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura

The Role of Global Labels in Few-Shot Classification and How to Infer Them

Ruohan Wang, Massimiliano Pontil, Carlo Ciliberto

Semialgebraic Representation of Monotone Deep Equilibrium Models and Applications to Certification

Tong Chen, Jean B Lasserre, Victor Magron, Edouard Pauwels

Deep Learning with Label Differential Privacy

Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang

Instance-Dependent Partial Label Learning

Ning Xu, Congyu Qiao, Xin Geng, Min-ling Zhang

GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction

Longyuan Li, Jian Yao, Li Wenliang, Tong He, Tianjun Xiao

Passive attention in artificial neural networks predicts human visual selectivity

Thomas Langlois, Haicheng Zhao, Erin Grant, Ishita Dasgupta, Tom Griffiths

Scaling Up Exact Neural Network Compression by ReLU Stability

Thiago Serra, Xin Yu, Abhinav Kumar, Srikumar Ramalingam

Least Square Calibration for Peer Reviews

Sijun Tan, Jibang Wu, Xiaohui Bei, Haifeng Xu

Federated Linear Contextual Bandits

Ruiquan Huang, Weiqiang Wu, Jing Yang, Cong Shen

Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks

Pascal Esser, Leena Chennuru Vankadara, Debarghya Ghoshdastidar

Topological Relational Learning on Graphs

Yuzhou Chen, Baris Coskunuzer, Yulia Gel

Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning

Hayeon Lee, Sewoong Lee, Song Chong, Sung Ju Hwang

MagNet: A Neural Network for Directed Graphs

Xitong Zhang, Yixuan He, Nathan Brugnone, Michael Perlmutter, Matthew Hirn

The staircase property: How hierarchical structure can guide deep learning

Emmanuel Abbe, Enric Boix-Adsera, Matthew S Brennan, Guy Bresler, Dheeraj Nagaraj

Streaming Belief Propagation for Community Detection

Yuchen Wu, Jakab Tardos, Mohammadhossein Bateni, André Linhares, Filipe Miguel Goncalves de Almeida

Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning

Christopher Hoang, Sungryull Sohn, Jongwook Choi, Wilka Carvalho, Honglak Lee

MAU: A Motion-Aware Unit for Video Prediction and Beyond

Zheng Chang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Yan Ye

Interpretable agent communication from scratch (with a generic visual processor emerging on the side)

Roberto Dessi, Eugene Kharitonov, Baroni Marco

Curriculum Disentangled Recommendation with Noisy Multi-feedback

Hong Chen, Yudong Chen, Xin Wang, Ruobing Xie, Rui Wang

Distilling Meta Knowledge on Heterogeneous Graph for Illicit Drug Trafficker Detection on Social Media

Yiyue Qian, Yiming Zhang, Yanfang (Fa Ye, Chuxu Zhang

Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm

Akash Kumar, Yuxin Chen, Adish Singla

Representation Costs of Linear Neural Networks: Analysis and Design

Zhen Dai, Mina Karzand, Nathan Srebro

PolarStream: Streaming Object Detection and Segmentation with Polar Pillars

Qi Chen, Sourabh Vora, Oscar Beijbom

Automated Discovery of Adaptive Attacks on Adversarial Defenses

Chengyuan Yao, Pavol Bielik, Petar Tsankov, Martin Vechev

Towards Sharper Generalization Bounds for Structured Prediction

Shaojie Li, Yong Liu

Are Transformers more robust than CNNs?

Yutong Bai, Jieru Mei, Alan L. Yuille, Cihang Xie

A Stochastic Newton Algorithm for Distributed Convex Optimization

Brian Bullins, Kshitij Patel, Ohad Shamir, Nathan Srebro, Blake E Woodworth

Bandit Learning with Delayed Impact of Actions

Wei Tang, Chien-Ju Ho, Yang Liu

Learning Generalized Gumbel-max Causal Mechanisms

Guy Lorberbom, Daniel D. Johnson, Chris J Maddison, Daniel Tarlow, Tamir Hazan

Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings

Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel

Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery

Lijun Ding, Liwei Jiang, Yudong Chen, Qing Qu, Zhihui Zhu

Optimal Rates for Nonparametric Density Estimation under Communication Constraints

Jayadev Acharya, Clement Canonne, Aditya Vikram Singh, Himanshu Tyagi

SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data

Alicia Curth, Changhee Lee, Mihaela van der Schaar

Improving Deep Learning Interpretability by Saliency Guided Training

Aya Abdelsalam Ismail, Hector Corrada Bravo, Soheil Feizi

Universal Semi-Supervised Learning

Zhuo Huang, Chao Xue, Bo Han, Jian Yang, Chen Gong

The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle

Fang Kong, Yueran Yang, Wei Chen, Shuai Li

Improving Compositionality of Neural Networks by Decoding Representations to Inputs

Mike Wu, Noah Goodman, Stefano Ermon

Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model

Jiangning Zhang, Chao Xu, Jian Li, Wenzhou Chen, Yabiao Wang

No RL, No Simulation: Learning to Navigate without Navigating

Meera Hahn, Devendra Singh Chaplot, Shubham Tulsiani, Mustafa Mukadam, James M. Rehg

The Limits of Optimal Pricing in the Dark

Quinlan Dawkins, Minbiao Han, Haifeng Xu

Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows

Brendan Ross, Jesse Cresswell

Joint Inference for Neural Network Depth and Dropout Regularization

Kishan K C, Rui Li, MohammadMahdi Gilany

The Elastic Lottery Ticket Hypothesis

Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Jingjing Liu

Shapley Residuals: Quantifying the limits of the Shapley value for explanations

Indra Kumar, Carlos Scheidegger, Suresh Venkatasubramanian, Sorelle Friedler

To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs

Thomas Scialom, Paul-Alexis Dray, Jacopo Staiano, Sylvain Lamprier, Benjamin Piwowarski

Fast Abductive Learning by Similarity-based Consistency Optimization

Yu-Xuan Huang, Wang-Zhou Dai, Le-Wen Cai, Stephen H Muggleton, Yuan Jiang