NeurIPS 2020

1,898 papers

Do Adversarially Robust ImageNet Models Transfer Better?

Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, Aleksander Madry

Restoring Negative Information in Few-Shot Object Detection

Yukuan Yang, Fangyun Wei, Miaojing Shi, Guoqi Li

Unsupervised Representation Learning by Invariance Propagation

Feng Wang, Huaping Liu, Di Guo, Sun Fuchun

Cross-Scale Internal Graph Neural Network for Image Super-Resolution

Shangchen Zhou, Jiawei Zhang, Wangmeng Zuo, Chen Change Loy

Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks

Wei-An Lin, Chun Pong Lau, Alexander Levine, Rama Chellappa, Soheil Feizi

Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition

Lin Chen, Qian Yu, Hannah Lawrence, Amin Karbasi

How hard is to distinguish graphs with graph neural networks?

Andreas Loukas

Input-Aware Dynamic Backdoor Attack

Tuan Anh Nguyen, Anh Tran

Inferring learning rules from animal decision-making

Zoe Ashwood, Nicholas A. Roy, Ji Hyun Bak, Jonathan W Pillow

Video Object Segmentation with Adaptive Feature Bank and Uncertain-Region Refinement

Yongqing Liang, Xin Li, Navid Jafari, Jim Chen

Online MAP Inference of Determinantal Point Processes

Aditya Bhaskara, Amin Karbasi, Silvio Lattanzi, Morteza Zadimoghaddam

Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases

Senthil Purushwalkam, Abhinav Gupta

An operator view of policy gradient methods

Dibya Ghosh, Marlos C. Machado, Nicolas Le Roux

Modeling Noisy Annotations for Crowd Counting

Jia Wan, Antoni B. Chan

Community detection using fast low-cardinality semidefinite programming

Po-Wei Wang, J. Zico Kolter

Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators

Takeshi Teshima, Isao Ishikawa, Koichi Tojo, Kenta Oono, Masahiro Ikeda

Self-Distillation Amplifies Regularization in Hilbert Space

Hossein Mobahi, Mehrdad Farajtabar, Peter L. Bartlett

Ode to an ODE

Krzysztof M Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques Slotine

Audeo: Audio Generation for a Silent Performance Video

Kun Su, Xiulong Liu, Eli Shlizerman

Breaking the Communication-Privacy-Accuracy Trilemma

Wei-Ning Chen, Peter Kairouz, Ayfer Ozgur

Optimal Private Median Estimation under Minimal Distributional Assumptions

Christos Tzamos, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Ilias Zadik

A Unified View of Label Shift Estimation

Saurabh Garg, Yifan Wu, Sivaraman Balakrishnan, Zachary Lipton

Neural Message Passing for Multi-Relational Ordered and Recursive Hypergraphs

Naganand Yadati

Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval

Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani

Reinforcement Learning for Control with Multiple Frequencies

Jongmin Lee, Byung-Jun Lee, Kee-eung Kim

UCLID-Net: Single View Reconstruction in Object Space

Benoit Guillard, Edoardo Remelli, Pascal Fua

Co-exposure Maximization in Online Social Networks

Sijing Tu, Cigdem Aslay, Aristides Gionis

Robust-Adaptive Control of Linear Systems: beyond Quadratic Costs

Edouard Leurent, Odalric-ambrym Maillard, Denis Efimov

Compact task representations as a normative model for higher-order brain activity

Severin Berger, Christian K. Machens

Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional Entropies

Itai Gat, Idan Schwartz, Alexander Schwing, Tamir Hazan

Finite Continuum-Armed Bandits

Solenne Gaucher

Adaptive Gradient Quantization for Data-Parallel SGD

Fartash Faghri, Iman Tabrizian, Ilia Markov, Dan Alistarh, Daniel M. Roy

Locally private non-asymptotic testing of discrete distributions is faster using interactive mechanisms

Thomas Berrett, Cristina Butucea

Causal analysis of Covid-19 Spread in Germany

Atalanti Mastakouri, Bernhard Schölkopf

A Novel Automated Curriculum Strategy to Solve Hard Sokoban Planning Instances

Dieqiao Feng, Carla P. Gomes, Bart Selman

Multi-label classification: do Hamming loss and subset accuracy really conflict with each other?

Guoqiang Wu, Jun Zhu

Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization

Haoliang Li, Yufei Wang, Renjie Wan, Shiqi Wang, Tie-Qiang Li

Unsupervised object-centric video generation and decomposition in 3D

Paul Henderson, Christoph H. Lampert

A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions

Yulong Lu, Jianfeng Lu

Learning Graph Structure With A Finite-State Automaton Layer

Daniel Johnson, Hugo Larochelle, Daniel Tarlow

Multimodal Graph Networks for Compositional Generalization in Visual Question Answering

Raeid Saqur, Karthik Narasimhan

Triple descent and the two kinds of overfitting: where & why do they appear?

Stéphane d'Ascoli, Levent Sagun, Giulio Biroli

Learning Dynamic Belief Graphs to Generalize on Text-Based Games

Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikuláš Zelinka, Marc-Antoine Rondeau

Lamina-specific neuronal properties promote robust, stable signal propagation in feedforward networks

Dongqi Han, Erik De Schutter, Sungho Hong

Fourier Spectrum Discrepancies in Deep Network Generated Images

Tarik Dzanic, Karan Shah, Freddie Witherden

Learning to summarize with human feedback

Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe

Normalizing Kalman Filters for Multivariate Time Series Analysis

Emmanuel de Bézenac, Syama Sundar Rangapuram, Konstantinos Benidis, Michael Bohlke-Schneider, Richard Kurle

Adversarial Self-Supervised Contrastive Learning

Minseon Kim, Jihoon Tack, Sung Ju Hwang

Stateful Posted Pricing with Vanishing Regret via Dynamic Deterministic Markov Decision Processes

Yuval Emek, Ron Lavi, Rad Niazadeh, Yangguang Shi

Adversarial Weight Perturbation Helps Robust Generalization

Dongxian Wu, Shu-Tao Xia, Yisen Wang

Learning from Mixtures of Private and Public Populations

Raef Bassily, Shay Moran, Anupama Nandi

Hold me tight! Influence of discriminative features on deep network boundaries

Guillermo Ortiz-Jimenez, Apostolos Modas, Seyed-Mohsen Moosavi, Pascal Frossard

Logarithmic Pruning is All You Need

Laurent Orseau, Marcus Hutter, Omar Rivasplata

Toward the Fundamental Limits of Imitation Learning

Nived Rajaraman, Lin Yang, Jiantao Jiao, Kannan Ramchandran

Partial Optimal Tranport with applications on Positive-Unlabeled Learning

Laetitia Chapel, Mokhtar Z. Alaya, Gilles Gasso

Partially View-aligned Clustering

Zhenyu Huang, Peng Hu, Joey Tianyi Zhou, Jiancheng Lv, Xi Peng

What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation

Vitaly Feldman, Chiyuan Zhang

A/B Testing in Dense Large-Scale Networks: Design and Inference

Preetam Nandy, Kinjal Basu, Shaunak Chatterjee, Ye Tu

Modular Meta-Learning with Shrinkage

Yutian Chen, Abram L. Friesen, Feryal Behbahani, Arnaud Doucet, David Budden

Geometric All-way Boolean Tensor Decomposition

Changlin Wan, Wennan Chang, Tong Zhao, Sha Cao, Chi Zhang

Implicit Regularization and Convergence for Weight Normalization

Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li

Model-based Policy Optimization with Unsupervised Model Adaptation

Jian Shen, Han Zhao, Weinan Zhang, Yong Yu

Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems

Songtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong

Intra-Processing Methods for Debiasing Neural Networks

Yash Savani, Colin White, Naveen Sundar Govindarajulu

Network-to-Network Translation with Conditional Invertible Neural Networks

Robin Rombach, Patrick Esser, Bjorn Ommer

ShiftAddNet: A Hardware-Inspired Deep Network

Haoran You, Xiaohan Chen, Yongan Zhang, Chaojian Li, Sicheng Li

Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning

Yifan Hu, Siqi Zhang, Xin Chen, Niao He

Minimax Value Interval for Off-Policy Evaluation and Policy Optimization

Nan Jiang, Jiawei Huang

Interventional Few-Shot Learning

Zhongqi Yue, Hanwang Zhang, Qianru Sun, Xian-Sheng Hua

Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes

Hao Chen, Lili Zheng, Raed AL Kontar, Garvesh Raskutti

Dual Instrumental Variable Regression

Krikamol Muandet, Arash Mehrjou, Si Kai Lee, Anant Raj

Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? --- A Neural Tangent Kernel Perspective

Kaixuan Huang, Yuqing Wang, Molei Tao, Tuo Zhao

Learning abstract structure for drawing by efficient motor program induction

Lucas Tian, Kevin Ellis, Marta Kryven, Josh Tenenbaum

Improving Policy-Constrained Kidney Exchange via Pre-Screening

Duncan McElfresh, Michael Curry, Tuomas Sandholm, John Dickerson

Weakly-Supervised Reinforcement Learning for Controllable Behavior

Lisa Lee, Ben Eysenbach, Ruslan Salakhutdinov, Shixiang (Shane) Gu, Chelsea Finn

Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions

Alessandro Epasto, Mohammad Mahdian, Vahab Mirrokni, Emmanouil Zampetakis

Identifying Learning Rules From Neural Network Observables

Aran Nayebi, Sanjana Srivastava, Surya Ganguli, Daniel L Yamins

Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function

Lingkai Kong, Molei Tao

The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes

Douwe Kiela, Hamed Firooz, Aravind Mohan, Vedanuj Goswami, Amanpreet Singh

Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is Sufficient

Ankit Pensia, Shashank Rajput, Alliot Nagle, Harit Vishwakarma, Dimitris Papailiopoulos

Structured Prediction for Conditional Meta-Learning

Ruohan Wang, Yiannis Demiris, Carlo Ciliberto

Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model

Raphaël Berthier, Francis R. Bach, Pierre Gaillard

Fighting Copycat Agents in Behavioral Cloning from Observation Histories

Chuan Wen, Jierui Lin, Trevor Darrell, Dinesh Jayaraman, Yang Gao

PRANK: motion Prediction based on RANKing

Yuriy Biktairov, Maxim Stebelev, Irina Rudenko, Oleh Shliazhko, Boris Yangel

Online Robust Regression via SGD on the l1 loss

Scott Pesme, Nicolas Flammarion

Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance

Ziv Goldfeld, Kristjan Greenewald, Kengo Kato

Attention-Gated Brain Propagation: How the brain can implement reward-based error backpropagation

Isabella Pozzi, Sander Bohte, Pieter Roelfsema

Riemannian Continuous Normalizing Flows

Emile Mathieu, Maximilian Nickel

Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance

Lior Yariv, Yoni Kasten, Dror Moran, Meirav Galun, Matan Atzmon

Bayesian Robust Optimization for Imitation Learning

Daniel Brown, Scott Niekum, Marek Petrik

Bayesian Multi-type Mean Field Multi-agent Imitation Learning

Fan Yang, Alina Vereshchaka, Changyou Chen, Wen Dong

Inverse Reinforcement Learning from a Gradient-based Learner

Giorgia Ramponi, Gianluca Drappo, Marcello Restelli

Information Maximization for Few-Shot Learning

Malik Boudiaf, Imtiaz Ziko, Jérôme Rony, Jose Dolz, Pablo Piantanida

Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification

Yulin Wang, Kangchen Lv, Rui Huang, Shiji Song, Le Yang

Consistent feature selection for analytic deep neural networks

Vu C Dinh, Lam S Ho

Inference Stage Optimization for Cross-scenario 3D Human Pose Estimation

Jianfeng Zhang, Xuecheng Nie, Jiashi Feng

Approximation Based Variance Reduction for Reparameterization Gradients

Tomas Geffner, Justin Domke

Practical Quasi-Newton Methods for Training Deep Neural Networks

Donald Goldfarb, Yi Ren, Achraf Bahamou

On Power Laws in Deep Ensembles

Ekaterina Lobacheva, Nadezhda Chirkova, Maxim Kodryan, Dmitry P Vetrov

Falcon: Fast Spectral Inference on Encrypted Data

Qian Lou, Wen-jie Lu, Cheng Hong, Lei Jiang