NeurIPS 2021

2,334 papers

DOCTOR: A Simple Method for Detecting Misclassification Errors

Federica Granese, Marco Romanelli, Daniele Gorla, Catuscia Palamidessi, Pablo Piantanida

Adrián Csiszárik, Péter Kőrösi-Szabó, Ákos Matszangosz, Gergely Papp, Dániel Varga

Robust Counterfactual Explanations on Graph Neural Networks

Mohit Bajaj, Lingyang Chu, Zi Yu Xue, Jian Pei, Lanjun Wang

Scalable Thompson Sampling using Sparse Gaussian Process Models

Sattar Vakili, Henry Moss, Artem Artemev, Vincent Dutordoir, Victor Picheny

Parameter Inference with Bifurcation Diagrams

Gregory Szep, Neil Dalchau, Attila Csikász-Nagy

A Topological Perspective on Causal Inference

Duligur Ibeling, Thomas Icard

Neural Regression, Representational Similarity, Model Zoology & Neural Taskonomy at Scale in Rodent Visual Cortex

Colin Conwell, David Mayo, Andrei Barbu, Michael Buice, George Alvarez

Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures

Zhaozhuo Xu, Zhao Song, Anshumali Shrivastava

Center Smoothing: Certified Robustness for Networks with Structured Outputs

Aounon Kumar, Tom Goldstein

Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks

Hanxun Huang, Yisen Wang, Sarah Erfani, Quanquan Gu, James Bailey

Redesigning the Transformer Architecture with Insights from Multi-particle Dynamical Systems

Subhabrata Dutta, Tanya Gautam, Soumen Chakrabarti, Tanmoy Chakraborty

Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction

Gal Dalal, Assaf Hallak, Steven Dalton, iuri frosio, Shie Mannor

RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem

Eric Liang, Zhanghao Wu, Michael Luo, Sven Mika, Joseph E Gonzalez

MarioNette: Self-Supervised Sprite Learning

Dmitriy Smirnov, MICHAEL GHARBI, Matthew Fisher, Vitor Guizilini, Alexei Efros

Factored Policy Gradients: Leveraging Structure for Efficient Learning in MOMDPs

Thomas Spooner, Nelson Vadori, Sumitra Ganesh

Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks

Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar

The Benefits of Implicit Regularization from SGD in Least Squares Problems

Difan Zou, Jingfeng Wu, Vladimir braverman, Quanquan Gu, Dean P. Foster

Posterior Collapse and Latent Variable Non-identifiability

Yixin Wang, David M. Blei, John P. Cunningham

A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration

Theo Bodrito, Alexandre Zouaoui, Jocelyn Chanussot, Julien Mairal

Blending Anti-Aliasing into Vision Transformer

Shengju Qian, Hao Shao, Yi Zhu, Mu Li, Jiaya Jia

Automatic Data Augmentation for Generalization in Reinforcement Learning

Roberta Raileanu, Maxwell Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus

Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions

Alejandro Carderera, Mathieu Besançon, Sebastian Pokutta

Accurate Point Cloud Registration with Robust Optimal Transport

Zhengyang Shen, Jean Feydy, Peirong Liu, Ariel H Curiale, Ruben San Jose Estepar

Imitation with Neural Density Models

Kuno Kim, Akshat Jindal, Yang Song, Jiaming Song, Yanan Sui

Equilibrium and non-Equilibrium regimes in the learning of Restricted Boltzmann Machines

Aurélien Decelle, Cyril Furtlehner, Beatriz Seoane

Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition

Lucas Liebenwein, Alaa Maalouf, Dan Feldman, Daniela Rus

Even your Teacher Needs Guidance: Ground-Truth Targets Dampen Regularization Imposed by Self-Distillation

Kenneth Borup, Lars N Andersen

Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation

Yunhao Tang, Tadashi Kozuno, Mark Rowland, Rémi Munos, Michal Valko

Efficient Equivariant Network

Lingshen He, Yuxuan Chen, Zhengyang Shen, Yiming Dong, Yisen Wang

PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning

Tao Yu, Cuiling Lan, Wenjun Zeng, Mingxiao Feng, Zhizheng Zhang

Domain Invariant Representation Learning with Domain Density Transformations

A. Tuan Nguyen, Toan Tran, Yarin Gal, Atilim Gunes Baydin

Learning where to learn: Gradient sparsity in meta and continual learning

Johannes von Oswald, Dominic Zhao, Seijin Kobayashi, Simon Schug, Massimo Caccia

Grounding Spatio-Temporal Language with Transformers

Tristan Karch, Laetitia Teodorescu, Katja Hofmann, Clément Moulin-Frier, Pierre-yves Oudeyer

Analysis of one-hidden-layer neural networks via the resolvent method

Vanessa Piccolo, Dominik Schröder

Distilling Object Detectors with Feature Richness

Du Zhixing, Rui Zhang, Ming Chang, xishan zhang, Shaoli Liu

SPANN: Highly-efficient Billion-scale Approximate Nearest Neighborhood Search

Qi Chen, Bing Zhao, Haidong Wang, Mingqin Li, Chuanjie Liu

Dataset Distillation with Infinitely Wide Convolutional Networks

Timothy Nguyen, Roman Novak, Lechao Xiao, Jaehoon Lee

Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems

Yiheng Lin, Yang Hu, Guanya Shi, Haoyuan Sun, Guannan Qu

Continuous Latent Process Flows

Ruizhi Deng, Marcus A Brubaker, Greg Mori, Andreas Lehrmann

When Is Unsupervised Disentanglement Possible?

Daniella Horan, Eitan Richardson, Yair Weiss

Matrix encoding networks for neural combinatorial optimization

Yeong-Dae Kwon, Jinho Choo, Iljoo Yoon, Minah Park, Duwon Park

Noisy Recurrent Neural Networks

Soon Hoe Lim, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney

Capturing implicit hierarchical structure in 3D biomedical images with self-supervised hyperbolic representations

Joy Hsu, Jeffrey Gu, Gong Wu, Wah Chiu, Serena Yeung

Differentially Private n-gram Extraction

Kunho Kim, Sivakanth Gopi, Janardhan Kulkarni, Sergey Yekhanin

CLDA: Contrastive Learning for Semi-Supervised Domain Adaptation

Ankit Singh

SketchGen: Generating Constrained CAD Sketches

Wamiq Para, Shariq Bhat, Paul Guerrero, Tom Kelly, Niloy Mitra

Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$

Yegor Klochkov, Nikita Zhivotovskiy

The Skellam Mechanism for Differentially Private Federated Learning

Naman Agarwal, Peter Kairouz, Ziyu Liu

Convex Polytope Trees

Mohammadreza Armandpour, Ali Sadeghian, Mingyuan Zhou

When False Positive is Intolerant: End-to-End Optimization with Low FPR for Multipartite Ranking

Peisong Wen, Qianqian Xu, Zhiyong Yang, Yuan He, Qingming Huang

Score-based Generative Neural Networks for Large-Scale Optimal Transport

Mara Daniels, Tyler Maunu, Paul Hand

Greedy Approximation Algorithms for Active Sequential Hypothesis Testing

Kyra Gan, Su Jia, Andrew Li

Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss

Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma

See More for Scene: Pairwise Consistency Learning for Scene Classification

Gongwei Chen, Xinhang Song, Bohan Wang, Shuqiang Jiang

Can contrastive learning avoid shortcut solutions?

Joshua W. Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka

CrypTen: Secure Multi-Party Computation Meets Machine Learning

Brian Knott, Shobha Venkataraman, Awni Hannun, Shubho Sengupta, Mark Ibrahim

Continuous vs. Discrete Optimization of Deep Neural Networks

Omer Elkabetz, Nadav Cohen

Offline RL Without Off-Policy Evaluation

David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna

Coupled Segmentation and Edge Learning via Dynamic Graph Propagation

Zhiding Yu, Rui Huang, Wonmin Byeon, Sifei Liu, Guilin Liu

Support vector machines and linear regression coincide with very high-dimensional features

Navid Ardeshir, Clayton Sanford, Daniel J. Hsu

Batch Normalization Orthogonalizes Representations in Deep Random Networks

Hadi Daneshmand, Amir Joudaki, Francis R. Bach

High-probability Bounds for Non-Convex Stochastic Optimization with Heavy Tails

Ashok Cutkosky, Harsh Mehta

Overcoming the Convex Barrier for Simplex Inputs

Harkirat Singh Behl, M. Pawan Kumar, Philip Torr, Krishnamurthy Dvijotham

Medical Dead-ends and Learning to Identify High-Risk States and Treatments

Mehdi Fatemi, Taylor W Killian, Jayakumar Subramanian, Marzyeh Ghassemi

Limiting fluctuation and trajectorial stability of multilayer neural networks with mean field training

Huy Tuan Pham, Phan-Minh Nguyen

Accurately Solving Rod Dynamics with Graph Learning

Han Shao, Tassilo Kugelstadt, Torsten Hädrich, Wojtek Palubicki, Jan Bender

MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers

Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck

Volume Rendering of Neural Implicit Surfaces

Lior Yariv, Jiatao Gu, Yoni Kasten, Yaron Lipman

Representation Learning Beyond Linear Prediction Functions

Ziping Xu, Ambuj Tewari

Beyond BatchNorm: Towards a Unified Understanding of Normalization in Deep Learning

Ekdeep S Lubana, Robert Dick, Hidenori Tanaka

Towards Robust Bisimulation Metric Learning

Mete Kemertas, Tristan Aumentado-Armstrong

Diverse Message Passing for Attribute with Heterophily

Liang Yang, Mengzhe Li, Liyang Liu, bingxin niu, Chuan Wang

Generalized Shape Metrics on Neural Representations

Alex H Williams, Erin Kunz, Simon Kornblith, Scott Linderman

Kernel Functional Optimisation

Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

Representation Learning for Event-based Visuomotor Policies

Sai Vemprala, Sami Mian, Ashish Kapoor

Neural Additive Models: Interpretable Machine Learning with Neural Nets

Rishabh Agarwal, Levi Melnick, Nicholas Frosst, Xuezhou Zhang, Ben Lengerich

Robust Online Correlation Clustering

Silvio Lattanzi, Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang, Rudy Zhou

Credit Assignment in Neural Networks through Deep Feedback Control

Alexander Meulemans, Matilde Tristany Farinha, Javier Garcia Ordonez, Pau Vilimelis Aceituno, João Sacramento

Online Facility Location with Multiple Advice

Matteo Almanza, Flavio Chierichetti, Silvio Lattanzi, Alessandro Panconesi, Giuseppe Re

Faster Directional Convergence of Linear Neural Networks under Spherically Symmetric Data

Dachao Lin, Ruoyu Sun, Zhihua Zhang

Flexible Option Learning

Martin Klissarov, Doina Precup

RoMA: Robust Model Adaptation for Offline Model-based Optimization

Sihyun Yu, Sungsoo Ahn, Le Song, Jinwoo Shin

Offline Meta Reinforcement Learning -- Identifiability Challenges and Effective Data Collection Strategies

Ron Dorfman, Idan Shenfeld, Aviv Tamar

Self-Adaptable Point Processes with Nonparametric Time Decays

Zhimeng Pan, Zheng Wang, Jeff M Phillips, Shandian Zhe

Aligning Silhouette Topology for Self-Adaptive 3D Human Pose Recovery

Ramesha Rakesh Mugaludi, Jogendra Nath Kundu, Varun Jampani, Venkatesh Babu R

Localization, Convexity, and Star Aggregation

Suhas Vijaykumar

MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps

Awais Muhammad, Fengwei Zhou, Chuanlong Xie, Jiawei Li, Sung-Ho Bae

Regime Switching Bandits

Xiang Zhou, Yi Xiong, Ningyuan Chen, Xuefeng GAO

Stability and Generalization of Bilevel Programming in Hyperparameter Optimization

Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang

Probing Inter-modality: Visual Parsing with Self-Attention for Vision-and-Language Pre-training

Hongwei Xue, Yupan Huang, Bei Liu, Houwen Peng, Jianlong Fu

Pruning Randomly Initialized Neural Networks with Iterative Randomization

Daiki Chijiwa, Shin'ya Yamaguchi, Yasutoshi Ida, Kenji Umakoshi, Tomohiro INOUE

Automatic Unsupervised Outlier Model Selection

Yue Zhao, Ryan Rossi, Leman Akoglu

Robust Regression Revisited: Acceleration and Improved Estimation Rates

Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian

Influence Patterns for Explaining Information Flow in BERT

Kaiji Lu, Zifan Wang, Piotr Mardziel, Anupam Datta

Probabilistic Attention for Interactive Segmentation

Prasad Gabbur, Manjot Bilkhu, Javier R. Movellan

LeadCache: Regret-Optimal Caching in Networks

Debjit Paria, Abhishek Sinha

Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration

Gavin Kerrigan, Padhraic Smyth, Mark Steyvers

Instance-dependent Label-noise Learning under a Structural Causal Model

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

Mixture weights optimisation for Alpha-Divergence Variational Inference

Kamélia Daudel, randal douc

EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback

Peter Richtarik, Igor Sokolov, Ilyas Fatkhullin