NeurIPS 2020

1,898 papers

Leap-Of-Thought: Teaching Pre-Trained Models to Systematically Reason Over Implicit Knowledge

Alon Talmor, Oyvind Tafjord, Peter Clark, Yoav Goldberg, Jonathan Berant

A mean-field analysis of two-player zero-sum games

Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant Rotskoff, Joan Bruna

Confidence sequences for sampling without replacement

Ian Waudby-Smith, Aaditya Ramdas

A Continuous-Time Mirror Descent Approach to Sparse Phase Retrieval

Fan Wu, Patrick Rebeschini

A Simple Language Model for Task-Oriented Dialogue

Ehsan Hosseini-Asl, Bryan McCann, Chien-Sheng Wu, Semih Yavuz, Richard Socher

PIE-NET: Parametric Inference of Point Cloud Edges

Xiaogang Wang, Yuelang Xu, Kai Xu, Andrea Tagliasacchi, Bin Zhou

GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis

Katja Schwarz, Yiyi Liao, Michael Niemeyer, Andreas Geiger

TorsionNet: A Reinforcement Learning Approach to Sequential Conformer Search

Tarun Gogineni, Ziping Xu, Exequiel Punzalan, Runxuan Jiang, Joshua Kammeraad

Bayesian Optimization of Risk Measures

Sait Cakmak, Raul Astudillo Marban, Peter Frazier, Enlu Zhou

Black-Box Ripper: Copying black-box models using generative evolutionary algorithms

Antonio Barbalau, Adrian Cosma, Radu Tudor Ionescu, Marius Popescu

A Class of Algorithms for General Instrumental Variable Models

Niki Kilbertus, Matt J Kusner, Ricardo Silva

FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs

Alekh Agarwal, Sham Kakade, Akshay Krishnamurthy, Wen Sun

The Primal-Dual method for Learning Augmented Algorithms

Etienne Bamas, Andreas Maggiori, Ola Svensson

Regression with reject option and application to kNN

Ahmed Zaoui, Christophe Denis, Mohamed Hebiri

On the universality of deep learning

Emmanuel Abbe, Colin Sandon

The Complete Lasso Tradeoff Diagram

Hua Wang, Yachong Yang, Zhiqi Bu, Weijie Su

OrganITE: Optimal transplant donor organ offering using an individual treatment effect

Jeroen Berrevoets, James Jordon, Ioana Bica, alexander gimson, Mihaela van der Schaar

A Theoretical Framework for Target Propagation

Alexander Meulemans, Francesco Carzaniga, Johan Suykens, João Sacramento, Benjamin F. Grewe

A General Large Neighborhood Search Framework for Solving Integer Linear Programs

Jialin Song, ravi lanka, Yisong Yue, Bistra Dilkina

GCOMB: Learning Budget-constrained Combinatorial Algorithms over Billion-sized Graphs

Sahil Manchanda, AKASH MITTAL, Anuj Dhawan, Sourav Medya, Sayan Ranu

Dialog without Dialog Data: Learning Visual Dialog Agents from VQA Data

Michael Cogswell, Jiasen Lu, Rishabh Jain, Stefan Lee, Devi Parikh

Learning Retrospective Knowledge with Reverse Reinforcement Learning

Shangtong Zhang, Vivek Veeriah, Shimon Whiteson

Batch Normalization Biases Residual Blocks Towards the Identity Function in Deep Networks

Soham De, Sam Smith

Beta R-CNN: Looking into Pedestrian Detection from Another Perspective

Zixuan Xu, Banghuai Li, Ye Yuan, Anhong Dang

Adversarial Bandits with Corruptions: Regret Lower Bound and No-regret Algorithm

Lin Yang, Mohammad Hajiesmaili, Mohammad Sadegh Talebi, Wing Shing Wong, John C.S. Lui

Joint Policy Search for Multi-agent Collaboration with Imperfect Information

Yuandong Tian, Qucheng Gong, Yu Jiang

Estimating Training Data Influence by Tracing Gradient Descent

Garima Pruthi, Frederick Liu, Satyen Kale, Mukund Sundararajan

Graduated Assignment for Joint Multi-Graph Matching and Clustering with Application to Unsupervised Graph Matching Network Learning

Runzhong Wang, Junchi Yan, Xiaokang Yang

Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision Processes

Yi Tian, Jian Qian, Suvrit Sra

Reinforcement Learning with Augmented Data

Misha Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel

Weston-Watkins Hinge Loss and Ordered Partitions

Yutong Wang, Clayton Scott

A Benchmark for Systematic Generalization in Grounded Language Understanding

Laura Ruis, Jacob Andreas, Marco Baroni, Diane Bouchacourt, Brenden M Lake

Compositional Zero-Shot Learning via Fine-Grained Dense Feature Composition

Dat Huynh, Ehsan Elhamifar

Graph Stochastic Neural Networks for Semi-supervised Learning

Haibo Wang, Chuan Zhou, Xin Chen, Jia Wu, Shirui Pan

A Robust Functional EM Algorithm for Incomplete Panel Count Data

Alexander Moreno, Zhenke Wu, Jamie Roslyn Yap, Cho Lam, David Wetter

The Adaptive Complexity of Maximizing a Gross Substitutes Valuation

Ron Kupfer, Sharon Qian, Eric Balkanski, Yaron Singer

Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs

Jianzhun Du, Joseph Futoma, Finale Doshi-velez

Comparator-Adaptive Convex Bandits

Dirk van der Hoeven, Ashok Cutkosky, Haipeng Luo

EvolveGraph: Multi-Agent Trajectory Prediction with Dynamic Relational Reasoning

Jiachen Li, Fan Yang, Masayoshi Tomizuka, Chiho Choi

Accelerating Reinforcement Learning through GPU Atari Emulation

Steven Dalton, iuri frosio

Universal Function Approximation on Graphs

Rickard Brüel Gabrielsson

Wisdom of the Ensemble: Improving Consistency of Deep Learning Models

Lijing Wang, Dipanjan Ghosh, Maria Gonzalez Diaz, Ahmed Farahat, Mahbubul Alam

Learning Linear Programs from Optimal Decisions

Yingcong Tan, Daria Terekhov, Andrew Delong

Learning Disentangled Representations and Group Structure of Dynamical Environments

Robin Quessard, Thomas Barrett, William Clements

Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphs

Hongyu Ren, Jure Leskovec

Counterfactual Prediction for Bundle Treatment

Hao Zou, Peng Cui, Bo Li, Zheyan Shen, Jianxin Ma

What Do Neural Networks Learn When Trained With Random Labels?

Hartmut Maennel, Ibrahim M Alabdulmohsin, Ilya O Tolstikhin, Robert Baldock, Olivier Bousquet

Can Temporal-Diﬀerence and Q-Learning Learn Representation? A Mean-Field Theory

Yufeng Zhang, Qi Cai, Zhuoran Yang, Yongxin Chen, Zhaoran Wang

NVAE: A Deep Hierarchical Variational Autoencoder

Arash Vahdat, Jan Kautz

HYDRA: Pruning Adversarially Robust Neural Networks

Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana

Flexible mean field variational inference using mixtures of non-overlapping exponential families

Jeffrey Spence

Recursive Inference for Variational Autoencoders

Minyoung Kim, Vladimir Pavlovic

Parameterized Explainer for Graph Neural Network

Dongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong

Polynomial-Time Computation of Optimal Correlated Equilibria in Two-Player Extensive-Form Games with Public Chance Moves and Beyond

Gabriele Farina, Tuomas Sandholm

Autoencoders that don't overfit towards the Identity

Harald Steck

An Efficient Framework for Clustered Federated Learning

Avishek Ghosh, Jichan Chung, Dong Yin, Kannan Ramchandran

Exponential ergodicity of mirror-Langevin diffusions

Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet

The Flajolet-Martin Sketch Itself Preserves Differential Privacy: Private Counting with Minimal Space

Adam Smith, Shuang Song, Abhradeep Guha Thakurta

Space-Time Correspondence as a Contrastive Random Walk

Allan Jabri, Andrew Owens, Alexei Efros

Unifying Activation- and Timing-based Learning Rules for Spiking Neural Networks

Jinseok Kim, Kyungsu Kim, Jae-Joon Kim

Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests

Sean Kulinski, Saurabh Bagchi, David I Inouye

Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search

Linnan Wang, Rodrigo Fonseca, Yuandong Tian

Asymptotically Optimal Exact Minibatch Metropolis-Hastings

Ruqi Zhang, A. Feder Cooper, Christopher M De Sa

Quantized Variational Inference

Amir Dib

Throughput-Optimal Topology Design for Cross-Silo Federated Learning

Othmane MARFOQ, CHUAN XU, Giovanni Neglia, Richard Vidal

Online Learning in Contextual Bandits using Gated Linear Networks

Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness

Dual-Free Stochastic Decentralized Optimization with Variance Reduction

Hadrien Hendrikx, Francis R. Bach, Laurent Massoulié

Untangling tradeoffs between recurrence and self-attention in artificial neural networks

Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal ALIAS PARTH GOYAL, Kyle Goyette, Yoshua Bengio

Neural Networks with Small Weights and Depth-Separation Barriers

Gal Vardi, Ohad Shamir

TaylorGAN: Neighbor-Augmented Policy Update Towards Sample-Efficient Natural Language Generation

Chun-Hsing Lin, Siang-Ruei Wu, Hung-yi Lee, Yun-Nung Chen

A new convergent variant of Q-learning with linear function approximation

Diogo Carvalho, Francisco S. Melo, Pedro Santos

Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement

Xin Liu, Josh Fromm, Shwetak Patel, Daniel McDuff

Near-Optimal Comparison Based Clustering

Michaël Perrot, Pascal Esser, Debarghya Ghoshdastidar

Effective Dimension Adaptive Sketching Methods for Faster Regularized Least-Squares Optimization

Jonathan Lacotte, Mert Pilanci

Self-Adaptive Training: beyond Empirical Risk Minimization

Lang Huang, Chao Zhang, Hongyang Zhang

Model Rubik’s Cube: Twisting Resolution, Depth and Width for TinyNets

Kai Han, Yunhe Wang, Qiulin Zhang, Wei Zhang, Chunjing XU

No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems

Nimit Sohoni, Jared Dunnmon, Geoffrey Angus, Albert Gu, Christopher Re

COPT: Coordinated Optimal Transport on Graphs

Yihe Dong, Will Sawin

Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings

Yu Chen, Lingfei Wu, Mohammed Zaki

Provably Robust Metric Learning

Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-jui Hsieh

Rethinking the Value of Labels for Improving Class-Imbalanced Learning

Yuzhe Yang, Zhi Xu

Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift

Remi Tachet des Combes, Han Zhao, Yu-Xiang Wang, Geoffrey J. Gordon

Weakly Supervised Deep Functional Maps for Shape Matching

Abhishek Sharma, Maks Ovsjanikov

BayReL: Bayesian Relational Learning for Multi-omics Data Integration

Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Xiaoning Qian

Online Bayesian Goal Inference for Boundedly Rational Planning Agents

Tan Zhi-Xuan, Jordyn Mann, Tom Silver, Josh Tenenbaum, Vikash K. Mansinghka

Generalization bound of globally optimal non-convex neural network training: Transportation map estimation by infinite dimensional Langevin dynamics

Taiji Suzuki

Transferable Calibration with Lower Bias and Variance in Domain Adaptation

Ximei Wang, Mingsheng Long, Jianmin Wang, Michael I. Jordan

Linear-Sample Learning of Low-Rank Distributions

Ayush Jain, Alon Orlitsky

Semialgebraic Optimization for Lipschitz Constants of ReLU Networks

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

Efficient Learning of Generative Models via Finite-Difference Score Matching

Tianyu Pang, Kun Xu, Chongxuan Li, Yang Song, Stefano Ermon

Efficient Planning in Large MDPs with Weak Linear Function Approximation

Roshan Shariff, Csaba Szepesvári

Modeling Shared responses in Neuroimaging Studies through MultiView ICA

Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort

Fair regression via plug-in estimator and recalibration with statistical guarantees

Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil

The Generalized Lasso with Nonlinear Observations and Generative Priors

Zhaoqiang Liu, Jonathan Scarlett

HRN: A Holistic Approach to One Class Learning

Wenpeng Hu, Mengyu Wang, Qi Qin, Jinwen Ma, Bing Liu

MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal Angles

Zhennan Wang, Canqun Xiang, Wenbin Zou, Chen Xu

Improving Auto-Augment via Augmentation-Wise Weight Sharing

Keyu Tian, CHEN LIN, Ming Sun, Luping Zhou, Junjie Yan

Handling Missing Data with Graph Representation Learning

Jiaxuan You, Xiaobai Ma, Yi Ding, Mykel J Kochenderfer, Jure Leskovec

Avoiding Side Effects By Considering Future Tasks

Victoria Krakovna, Laurent Orseau, Richard Ngo, Miljan Martic, Shane Legg

Acceleration with a Ball Optimization Oracle

Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee