NeurIPS 2020

1,898 papers

Greedy inference with structure-exploiting lazy maps

Michael Brennan, Daniele Bigoni, Olivier Zahm, Alessio Spantini, Youssef Marzouk

Learning the Geometry of Wave-Based Imaging

Konik Kothari, Maarten de Hoop, Ivan Dokmanić

Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite Matrices

John C. Duchi, Oliver Hinder, Andrew Naber, Yinyu Ye

Theory-Inspired Path-Regularized Differential Network Architecture Search

Pan Zhou, Caiming Xiong, Richard Socher, Steven Chu Hong Hoi

Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes

Andrew Foong, Wessel Bruinsma, Jonathan Gordon, Yann Dubois, James Requeima

Adversarial Distributional Training for Robust Deep Learning

Yinpeng Dong, Zhijie Deng, Tianyu Pang, Jun Zhu, Hang Su

From Finite to Countable-Armed Bandits

Anand Kalvit, Assaf J. Zeevi

An efficient nonconvex reformulation of stagewise convex optimization problems

Rudy R Bunel, Oliver Hinder, Srinadh Bhojanapalli, Krishnamurthy Dvijotham

Self-Supervised Generative Adversarial Compression

Chong Yu, Jeff Pool

Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes

Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam

Variational Bayesian Monte Carlo with Noisy Likelihoods

Luigi Acerbi

One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL

Saurabh Kumar, Aviral Kumar, Sergey Levine, Chelsea Finn

Learning Invariants through Soft Unification

Nuri Cingillioglu, Alessandra Russo

Rotation-Invariant Local-to-Global Representation Learning for 3D Point Cloud

SEOHYUN KIM, JaeYoo Park, Bohyung Han

Multi-label Contrastive Predictive Coding

Jiaming Song, Stefano Ermon

Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice

Shufan Wang, Jian Li, Shiqiang Wang

Adversarial Blocking Bandits

Nicholas Bishop, Hau Chan, Debmalya Mandal, Long Tran-Thanh

Robust Reinforcement Learning via Adversarial training with Langevin Dynamics

Parameswaran Kamalaruban, Yu-Ting Huang, Ya-Ping Hsieh, Paul Rolland, Cheng Shi

Novelty Search in Representational Space for Sample Efficient Exploration

Ruo Yu Tao, Vincent Francois-Lavet, Joelle Pineau

Posterior Re-calibration for Imbalanced Datasets

Junjiao Tian, Yen-Cheng Liu, Nathaniel Glaser, Yen-Chang Hsu, Zsolt Kira

Cycle-Contrast for Self-Supervised Video Representation Learning

Quan Kong, Wenpeng Wei, Ziwei Deng, Tomoaki Yoshinaga, Tomokazu Murakami

Towards Learning Convolutions from Scratch

Behnam Neyshabur

Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search

Jaehyeon Kim, Sungwon Kim, Jungil Kong, Sungroh Yoon

A Scalable Approach for Privacy-Preserving Collaborative Machine Learning

Jinhyun So, Basak Guler, Salman Avestimehr

Optimal Robustness-Consistency Trade-offs for Learning-Augmented Online Algorithms

Alexander Wei, Fred Zhang

Demystifying Orthogonal Monte Carlo and Beyond

Han Lin, Haoxian Chen, Krzysztof M Choromanski, Tianyi Zhang, Clement Laroche

Subgraph Neural Networks

Emily Alsentzer, Samuel Finlayson, Michelle Li, Marinka Zitnik

The Devil is in the Detail: A Framework for Macroscopic Prediction via Microscopic Models

Yingxiang Yang, Negar Kiyavash, Le Song, Niao He

Learning from Aggregate Observations

Yivan Zhang, Nontawat Charoenphakdee, Zhenguo Wu, Masashi Sugiyama

Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework

Wanxin Jin, Zhaoran Wang, Zhuoran Yang, Shaoshuai Mou

Improving Generalization in Reinforcement Learning with Mixture Regularization

KAIXIN WANG, Bingyi Kang, Jie Shao, Jiashi Feng

Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree

Peizhong Ju, Xiaojun Lin, Jia Liu

Deep Transformation-Invariant Clustering

Tom Monnier, Thibault Groueix, Mathieu Aubry

Secretary and Online Matching Problems with Machine Learned Advice

Antonios Antoniadis, Themis Gouleakis, Pieter Kleer, Pavel Kolev

Distributionally Robust Parametric Maximum Likelihood Estimation

Viet Anh Nguyen, Xuhui Zhang, Jose Blanchet, Angelos Georghiou

Deep Statistical Solvers

Balthazar Donon, Zhengying Liu, Wenzhuo LIU, Isabelle Guyon, Antoine Marot

Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics

Minhae Kwon, Saurabh Daptardar, Paul R. Schrater, Xaq Pitkow

Off-Policy Interval Estimation with Lipschitz Value Iteration

Ziyang Tang, Yihao Feng, Na Zhang, Jian Peng, Qiang Liu

Neural Star Domain as Primitive Representation

Yuki Kawana, Yusuke Mukuta, Tatsuya Harada

Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards

Vrettos Moulos

On the Theory of Transfer Learning: The Importance of Task Diversity

Nilesh Tripuraneni, Michael I. Jordan, Chi Jin

Detecting Hands and Recognizing Physical Contact in the Wild

Supreeth Narasimhaswamy, Trung Nguyen, Minh Hoai Nguyen

Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification

Lynton Ardizzone, Radek Mackowiak, Carsten Rother, Ullrich Köthe

Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent

Dimitris Fotakis, Thanasis Lianeas, Georgios Piliouras, Stratis Skoulakis

Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows

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

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs

Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu

Boosting Adversarial Training with Hypersphere Embedding

Tianyu Pang, Xiao Yang, Yinpeng Dong, Kun Xu, Jun Zhu

Critic Regularized Regression

Ziyu Wang, Alexander Novikov, Konrad Zolna, Josh S Merel, Jost Tobias Springenberg

Generalized Hindsight for Reinforcement Learning

Alexander Li, Lerrel Pinto, Pieter Abbeel

Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study

Assaf Dauber, Meir Feder, Tomer Koren, Roi Livni

Estimating weighted areas under the ROC curve

Andreas Maurer, Massimiliano Pontil

No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium

Andrea Celli, Alberto Marchesi, Gabriele Farina, Nicola Gatti

Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks

Zhou Fan, Zhichao Wang

ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping

Cher Bass, Mariana da Silva, Carole Sudre, Petru-Daniel Tudosiu, Stephen Smith

Language and Visual Entity Relationship Graph for Agent Navigation

Yicong Hong, Cristian Rodriguez, Yuankai Qi, Qi Wu, Stephen Gould

The NetHack Learning Environment

Heinrich Küttler, Nantas Nardelli, Alexander Miller, Roberta Raileanu, Marco Selvatici

MRI Banding Removal via Adversarial Training

Aaron Defazio, Tullie Murrell, Michael Recht

Automatic Curriculum Learning through Value Disagreement

Yunzhi Zhang, Pieter Abbeel, Lerrel Pinto

Geometric Exploration for Online Control

Orestis Plevrakis, Elad Hazan

An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods

Yanli Liu, Kaiqing Zhang, Tamer Basar, Wotao Yin

Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization

Jianyu Wang, Qinghua Liu, Hao Liang, Gauri Joshi, H. Vincent Poor

Part-dependent Label Noise: Towards Instance-dependent Label Noise

Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Mingming Gong

Learning Certified Individually Fair Representations

Anian Ruoss, Mislav Balunovic, Marc Fischer, Martin Vechev

Heuristic Domain Adaptation

Shuhao Cui, Xuan Jin, Shuhui Wang, Yuan He, Qingming Huang

Differentiable Augmentation for Data-Efficient GAN Training

Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, Song Han

Graph Geometry Interaction Learning

Shichao Zhu, Shirui Pan, Chuan Zhou, Jia Wu, Yanan Cao

Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Matthew Tancik, Pratul Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan

Hierarchical nucleation in deep neural networks

Diego Doimo, Aldo Glielmo, Alessio Ansuini, Alessandro Laio

Adaptive Learning of Rank-One Models for Efficient Pairwise Sequence Alignment

Govinda Kamath, Tavor Baharav, Ilan Shomorony

Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness

Jeremiah Liu, Zi Lin, Shreyas Padhy, Dustin Tran, Tania Bedrax Weiss

Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian

Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay

Rotated Binary Neural Network

Mingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang, Yan Wang

Implicit Neural Representations with Periodic Activation Functions

Vincent Sitzmann, Julien Martel, Alexander Bergman, David Lindell, Gordon Wetzstein

Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free

Haotao Wang, Tianlong Chen, Shupeng Gui, TingKuei Hu, Ji Liu

Online Neural Connectivity Estimation with Noisy Group Testing

Anne Draelos, John C. Pearson

Multi-Plane Program Induction with 3D Box Priors

Yikai Li, Jiayuan Mao, Xiuming Zhang, Bill Freeman, Josh Tenenbaum

Preference learning along multiple criteria: A game-theoretic perspective

Kush Bhatia, Ashwin Pananjady, Peter L. Bartlett, Anca Dragan, Martin J. Wainwright

HyNet: Learning Local Descriptor with Hybrid Similarity Measure and Triplet Loss

Yurun Tian, Axel Barroso Laguna, Tony Ng, Vassileios Balntas, Krystian Mikolajczyk

Generating Correct Answers for Progressive Matrices Intelligence Tests

Niv Pekar, Yaniv Benny, Lior Wolf

A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems

Jiawei Zhang, Peijun Xiao, Ruoyu Sun, Zhi-Quan Luo, Zhiquan Luo

On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method

Ye He, Krishnakumar Balasubramanian, Murat A Erdogdu

Strictly Batch Imitation Learning by Energy-based Distribution Matching

Daniel Jarrett, Ioana Bica, Mihaela van der Schaar

Exactly Computing the Local Lipschitz Constant of ReLU Networks

Matt Jordan, Alexandros G Dimakis

Training Stronger Baselines for Learning to Optimize

Tianlong Chen, Weiyi Zhang, Zhou Jingyang, Shiyu Chang, Sijia Liu

Fair regression with Wasserstein barycenters

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

Understanding the Role of Training Regimes in Continual Learning

Seyed Iman Mirzadeh, Mehrdad Farajtabar, Razvan Pascanu, Hassan Ghasemzadeh

Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks

Roman Pogodin, Peter E. Latham

A simple normative network approximates local non-Hebbian learning in the cortex

Siavash Golkar, David Lipshutz, Yanis Bahroun, Anirvan Sengupta, Dmitri B. Chklovskii

Interior Point Solving for LP-based prediction+optimisation

Jayanta Mandi, Tias Guns

Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning

Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng

RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning

Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez

Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE

Ding Zhou, Xue-xin Wei

Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC

Arun Ganesh, Kunal Talwar

Self-Supervised Few-Shot Learning on Point Clouds

Charu Sharma, Manohar Kaul

Swapping Autoencoder for Deep Image Manipulation

Taesung Park, Jun-Yan Zhu, Oliver Wang, Jingwan Lu, Eli Shechtman

Efficient active learning of sparse halfspaces with arbitrary bounded noise

Chicheng Zhang, Jie Shen, Pranjal Awasthi

Training Linear Finite-State Machines

Arash Ardakani, Amir Ardakani, Warren Gross

Small Nash Equilibrium Certificates in Very Large Games

Brian Zhang, Tuomas Sandholm

Auxiliary Task Reweighting for Minimum-data Learning

Baifeng Shi, Judy Hoffman, Kate Saenko, Trevor Darrell, Huijuan Xu

Implicit Distributional Reinforcement Learning

Yuguang Yue, Zhendong Wang, Mingyuan Zhou