NeurIPS 2021

2,334 papers

STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data

Zhi Zhou, Lan-Zhe Guo, Zhanzhan Cheng, Yu-feng Li, Shiliang Pu

Margin-Independent Online Multiclass Learning via Convex Geometry

Guru Guruganesh, Allen Liu, Jon Schneider, Joshua Wang

Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization

Jianhao Wang, Zhizhou Ren, Beining Han, Jianing Ye, Chongjie Zhang

Differentiable Optimization of Generalized Nondecomposable Functions using Linear Programs

Zihang Meng, Lopamudra Mukherjee, Yichao Wu, Vikas Singh, Sathya Ravi

On Optimal Interpolation in Linear Regression

Eduard Oravkin, Patrick Rebeschini

Optimal Gradient-based Algorithms for Non-concave Bandit Optimization

Baihe Huang, Kaixuan Huang, Sham Kakade, Jason Lee, Qi Lei

Balanced Chamfer Distance as a Comprehensive Metric for Point Cloud Completion

Tong Wu, Liang Pan, Junzhe Zhang, Tai WANG, Ziwei Liu

Can multi-label classification networks know what they don’t know?

Haoran Wang, Weitang Liu, Alex Bocchieri, Yixuan Li

Bandit Quickest Changepoint Detection

Aditya Gopalan, Braghadeesh Lakshminarayanan, Venkatesh Saligrama

Global Convergence to Local Minmax Equilibrium in Classes of Nonconvex Zero-Sum Games

Tanner Fiez, Lillian Ratliff, Eric Mazumdar, Evan Faulkner, Adhyyan Narang

Learning Robust Hierarchical Patterns of Human Brain across Many fMRI Studies

Dushyant Sahoo, Christos Davatzikos

TAAC: Temporally Abstract Actor-Critic for Continuous Control

Haonan Yu, Wei Xu, Haichao Zhang

Cross-view Geo-localization with Layer-to-Layer Transformer

Hongji Yang, Xiufan Lu, Yingying Zhu

On the Expected Complexity of Maxout Networks

Hanna Tseran, Guido F. Montufar

Differentially Private Sampling from Distributions

Sofya Raskhodnikova, Satchit Sivakumar, Adam Smith, Marika Swanberg

Time-series Generation by Contrastive Imitation

Daniel Jarrett, Ioana Bica, Mihaela van der Schaar

COMBO: Conservative Offline Model-Based Policy Optimization

Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine

Deep Networks Provably Classify Data on Curves

Tingran Wang, Sam Buchanan, Dar Gilboa, John Wright

Nearly-Tight and Oblivious Algorithms for Explainable Clustering

Buddhima Gamlath, Xinrui Jia, Adam Polak, Ola Svensson

Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training

Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu

Stronger NAS with Weaker Predictors

Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu

Powerpropagation: A sparsity inducing weight reparameterisation

Jonathan Schwarz, Siddhant Jayakumar, Razvan Pascanu, Yee W. Teh, Peter E. Latham

Do Transformers Really Perform Badly for Graph Representation?

Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke

Unsupervised Object-Level Representation Learning from Scene Images

Jiahao Xie, Xiaohang Zhan, Ziwei Liu, Yew Soon Ong, Chen Change Loy

Scalars are universal: Equivariant machine learning, structured like classical physics

Soledad Villar, David W Hogg, Kate Storey-Fisher, Weichi Yao, Ben Blum-Smith

A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance

Sudeep Salgia, Sattar Vakili, Qing Zhao

On Contrastive Representations of Stochastic Processes

Emile Mathieu, Adam Foster, Yee W. Teh

A Universal Law of Robustness via Isoperimetry

Sébastien Bubeck, Mark Sellke

GraphFormers: GNN-nested Transformers for Representation Learning on Textual Graph

Junhan Yang, Zheng Liu, Shitao Xiao, Chaozhuo Li, Defu Lian

Unsupervised Domain Adaptation with Dynamics-Aware Rewards in Reinforcement Learning

Jinxin Liu, Hao Shen, Donglin Wang, Yachen Kang, Qiangxing Tian

Achieving Rotational Invariance with Bessel-Convolutional Neural Networks

Valentin Delchevalerie, Adrien Bibal, Benoît Frénay, Alexandre Mayer

Your head is there to move you around: Goal-driven models of the primate dorsal pathway

Patrick Mineault, Shahab Bakhtiari, Blake Richards, Christopher Pack

Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning

Jannik Kossen, Neil Band, Clare Lyle, Aidan N Gomez, Thomas Rainforth

Stateful Strategic Regression

Keegan Harris, Hoda Heidari, Steven Z. Wu

3D Siamese Voxel-to-BEV Tracker for Sparse Point Clouds

Le Hui, Lingpeng Wang, Mingmei Cheng, Jin Xie, Jian Yang

Making a (Counterfactual) Difference One Rationale at a Time

Mitchell Plyler, Michael Green, Min Chi

Learning a Single Neuron with Bias Using Gradient Descent

Gal Vardi, Gilad Yehudai, Ohad Shamir

Adversarially robust learning for security-constrained optimal power flow

Priya Donti, Aayushya Agarwal, Neeraj Vijay Bedmutha, Larry Pileggi, J. Zico Kolter

Breaking the centralized barrier for cross-device federated learning

Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank Reddi

Why Do Better Loss Functions Lead to Less Transferable Features?

Simon Kornblith, Ting Chen, Honglak Lee, Mohammad Norouzi

Online Convex Optimization with Continuous Switching Constraint

Guanghui Wang, Yuanyu Wan, Tianbao Yang, Lijun Zhang

On Path Integration of Grid Cells: Group Representation and Isotropic Scaling

Ruiqi Gao, Jianwen Xie, Xue-xin Wei, Song-chun Zhu, Ying Nian Wu

Few-Round Learning for Federated Learning

Younghyun Park, Dong-Jun Han, Do-Yeon Kim, Jun Seo, Jaekyun Moon

MobILE: Model-Based Imitation Learning From Observation Alone

Rahul Kidambi, Jonathan Chang, Wen Sun

Topographic VAEs learn Equivariant Capsules

T. Anderson Keller, Max Welling

Asymptotically Exact Error Characterization of Offline Policy Evaluation with Misspecified Linear Models

Kohei Miyaguchi

Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme

Shaojie Li, Jie Wu, Xuefeng Xiao, Fei Chao, Xudong Mao

Post-Contextual-Bandit Inference

Aurelien Bibaut, Maria Dimakopoulou, Nathan Kallus, Antoine Chambaz, Mark van der Laan

Open Rule Induction

Wanyun Cui, Xingran Chen

ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias

Yufei Xu, Qiming ZHANG, Jing Zhang, Dacheng Tao

Towards Best-of-All-Worlds Online Learning with Feedback Graphs

Liad Erez, Tomer Koren

Continual World: A Robotic Benchmark For Continual Reinforcement Learning

Maciej Wołczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś

Entropy-based adaptive Hamiltonian Monte Carlo

Marcel Hirt, Michalis K. Titsias, Petros Dellaportas

Stylized Dialogue Generation with Multi-Pass Dual Learning

Jinpeng Li, Yingce Xia, Rui Yan, Hongda Sun, Dongyan Zhao

How Powerful are Performance Predictors in Neural Architecture Search?

Colin White, Arber Zela, Robin Ru, Yang Liu, Frank Hutter

End-to-end Multi-modal Video Temporal Grounding

Yi-Wen Chen, Yi-Hsuan Tsai, Ming-Hsuan Yang

Turing Completeness of Bounded-Precision Recurrent Neural Networks

Stephen Chung, Hava T. Siegelmann

Adaptive Online Packing-guided Search for POMDPs

Chenyang Wu, Guoyu Yang, Zongzhang Zhang, Yang Yu, Dong Li

Efficient constrained sampling via the mirror-Langevin algorithm

Kwangjun Ahn, Sinho Chewi

Conditional Generation Using Polynomial Expansions

Grigorios Chrysos, Markos Georgopoulos, Yannis Panagakis

On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations

Tim G. J. Rudner, Cong Lu, Michael A Osborne, Yarin Gal, Yee W. Teh

Parametrized Quantum Policies for Reinforcement Learning

Sofiene Jerbi, Casper Gyurik, Simon Marshall, Hans Briegel, Vedran Dunjko

Minimax Regret for Stochastic Shortest Path

Alon Cohen, Yonathan Efroni, Yishay Mansour, Aviv Rosenberg

Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning

Junsu Kim, Younggyo Seo, Jinwoo Shin

No-regret Online Learning over Riemannian Manifolds

Xi Wang, Zhipeng Tu, Yiguang Hong, Yingyi Wu, Guodong Shi

Efficient Generalization with Distributionally Robust Learning

Soumyadip Ghosh, Mark Squillante, Ebisa Wollega

Implicit Sparse Regularization: The Impact of Depth and Early Stopping

Jiangyuan Li, Thanh Nguyen, Chinmay Hegde, Ka Wai Wong

On the Sample Complexity of Privately Learning Axis-Aligned Rectangles

Menachem Sadigurschi, Uri Stemmer

CBP: backpropagation with constraint on weight precision using a pseudo-Lagrange multiplier method

Guhyun Kim, Doo Seok Jeong

Robustness via Uncertainty-aware Cycle Consistency

Uddeshya Upadhyay, Yanbei Chen, Zeynep Akata

Momentum Centering and Asynchronous Update for Adaptive Gradient Methods

Juntang Zhuang, Yifan Ding, Tommy Tang, Nicha Dvornek, Sekhar C Tatikonda

Independent mechanism analysis, a new concept?

Luigi Gresele, Julius von Kügelgen, Vincent Stimper, Bernhard Schölkopf, Michel Besserve

Logarithmic Regret from Sublinear Hints

Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit

Variational Bayesian Reinforcement Learning with Regret Bounds

Brendan O'Donoghue

Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization

Gaspard Beugnot, Julien Mairal, Alessandro Rudi

Towards mental time travel: a hierarchical memory for reinforcement learning agents

Andrew Lampinen, Stephanie Chan, Andrea Banino, Felix Hill

ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers

Husheng Han, Kaidi Xu, Xing Hu, Xiaobing Chen, Ling Liang

Towards Sample-efficient Overparameterized Meta-learning

Yue Sun, Adhyyan Narang, Ibrahim Gulluk, Samet Oymak, Maryam Fazel

Fair Sequential Selection Using Supervised Learning Models

Mohammad Mahdi Khalili, Xueru Zhang, Mahed Abroshan

An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers

Ramakrishna Vedantam, David Lopez-paz, David J Schwab

ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning

Guocheng Qian, Hasan Hammoud, Guohao Li, Ali Thabet, Bernard Ghanem

Unsupervised Part Discovery from Contrastive Reconstruction

Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi

Post-Training Quantization for Vision Transformer

Zhenhua Liu, Yunhe Wang, Kai Han, Wei Zhang, Siwei Ma

Individual Privacy Accounting via a Rényi Filter

Vitaly Feldman, Tijana Zrnic

Natural continual learning: success is a journey, not (just) a destination

Ta-Chu Kao, Kristopher Jensen, Gido van de Ven, Alberto Bernacchia, Guillaume Hennequin

Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms

Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Hadrien Hendrikx

Encoding Robustness to Image Style via Adversarial Feature Perturbations

Manli Shu, Zuxuan Wu, Micah Goldblum, Tom Goldstein

No Regrets for Learning the Prior in Bandits

Soumya Basu, Branislav Kveton, Manzil Zaheer, Csaba Szepesvári

Transformers Generalize DeepSets and Can be Extended to Graphs & Hypergraphs

Jinwoo Kim, Saeyoon Oh, Seunghoon Hong

RelaySum for Decentralized Deep Learning on Heterogeneous Data

Thijs Vogels, Lie He, Anastasiia Koloskova, Sai Praneeth Karimireddy, Tao LIN

Dynamical Wasserstein Barycenters for Time-series Modeling

Kevin Cheng, Shuchin Aeron, Michael C Hughes, Eric L Miller

RIM: Reliable Influence-based Active Learning on Graphs

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

Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data

Qi Zhu, Natalia Ponomareva, Jiawei Han, Bryan Perozzi

Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization

Shicong Cen, Yuting Wei, Yuejie Chi

Garment4D: Garment Reconstruction from Point Cloud Sequences

Fangzhou Hong, Liang Pan, Zhongang Cai, Ziwei Liu

You Are the Best Reviewer of Your Own Papers: An Owner-Assisted Scoring Mechanism

Weijie Su

On Memorization in Probabilistic Deep Generative Models

Gerrit van den Burg, Chris Williams

Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis

Yutong He, Dingjie Wang, Nicholas Lai, William Zhang, Chenlin Meng

Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach

Fan Yang, Kai He, Linxiao Yang, Hongxia Du, Jingbang Yang

Faster Neural Network Training with Approximate Tensor Operations

Menachem Adelman, Kfir Levy, Ido Hakimi, Mark Silberstein