NeurIPS 2020

1,898 papers

BOSS: Bayesian Optimization over String Spaces

Henry Moss, David Leslie, Daniel Beck, Javier Gonzalez, Paul Rayson

Active Invariant Causal Prediction: Experiment Selection through Stability

Juan L. Gamella, Christina Heinze-Deml

Efficient Algorithms for Device Placement of DNN Graph Operators

Jakub M Tarnawski, Amar Phanishayee, Nikhil Devanur, Divya Mahajan, Fanny Nina Paravecino

System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina

Cornelius Schröder, David Klindt, Sarah Strauss, Katrin Franke, Matthias Bethge

Certified Monotonic Neural Networks

Xingchao Liu, Xing Han, Na Zhang, Qiang Liu

Robust Sequence Submodular Maximization

Gamal Sallam, Zizhan Zheng, Jie Wu, Bo Ji

Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates

Kaiwen Zhou, Anthony Man-Cho So, James Cheng

Neural Sparse Representation for Image Restoration

Yuchen Fan, Jiahui Yu, Yiqun Mei, Yulun Zhang, Yun Fu

Why are Adaptive Methods Good for Attention Models?

Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank Reddi

Deep Rao-Blackwellised Particle Filters for Time Series Forecasting

Richard Kurle, Syama Sundar Rangapuram, Emmanuel de Bézenac, Stephan Günnemann, Jan Gasthaus

Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning

Luca Oneto, Michele Donini, Giulia Luise, Carlo Ciliberto, Andreas Maurer

Learning Augmented Energy Minimization via Speed Scaling

Etienne Bamas, Andreas Maggiori, Lars Rohwedder, Ola Svensson

First Order Constrained Optimization in Policy Space

Yiming Zhang, Quan Vuong, Keith Ross

A kernel test for quasi-independence

Tamara Fernandez, Wenkai Xu, Marc Ditzhaus, Arthur Gretton

Information Theoretic Regret Bounds for Online Nonlinear Control

Sham Kakade, Akshay Krishnamurthy, Kendall Lowrey, Motoya Ohnishi, Wen Sun

Optimizing Mode Connectivity via Neuron Alignment

Norman Tatro, Pin-Yu Chen, Payel Das, Igor Melnyk, Prasanna Sattigeri

Calibrating Deep Neural Networks using Focal Loss

Jishnu Mukhoti, Viveka Kulharia, Amartya Sanyal, Stuart Golodetz, Philip Torr

Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss

Shuang Qiu, Xiaohan Wei, Zhuoran Yang, Jieping Ye, Zhaoran Wang

Learning Strategy-Aware Linear Classifiers

Yiling Chen, Yang Liu, Chara Podimata

Meta-Gradient Reinforcement Learning with an Objective Discovered Online

Zhongwen Xu, Hado P van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder P. Singh

Robust Multi-Object Matching via Iterative Reweighting of the Graph Connection Laplacian

Yunpeng Shi, Shaohan Li, Gilad Lerman

Distributionally Robust Local Non-parametric Conditional Estimation

Viet Anh Nguyen, Fan Zhang, Jose Blanchet, Erick Delage, Yinyu Ye

Displacement-Invariant Matching Cost Learning for Accurate Optical Flow Estimation

Jianyuan Wang, Yiran Zhong, Yuchao Dai, Kaihao Zhang, Pan Ji

Learning to Incentivize Other Learning Agents

Jiachen Yang, Ang Li, Mehrdad Farajtabar, Peter Sunehag, Edward Hughes

Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage Decomposition

Zihan Zhang, Yuan Zhou, Xiangyang Ji

Nonasymptotic Guarantees for Spiked Matrix Recovery with Generative Priors

Jorio Cocola, Paul Hand, Vlad Voroninski

Supermasks in Superposition

Mitchell Wortsman, Vivek Ramanujan, Rosanne Liu, Aniruddha Kembhavi, Mohammad Rastegari

Finite Versus Infinite Neural Networks: an Empirical Study

Jaehoon Lee, Samuel Schoenholz, Jeffrey Pennington, Ben Adlam, Lechao Xiao

Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control

Zhiyuan Xu, Kun Wu, Zhengping Che, Jian Tang, Jieping Ye

COBE: Contextualized Object Embeddings from Narrated Instructional Video

Gedas Bertasius, Lorenzo Torresani

Sharp uniform convergence bounds through empirical centralization

Cyrus Cousins, Matteo Riondato

Distributionally Robust Federated Averaging

Yuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi

A Randomized Algorithm to Reduce the Support of Discrete Measures

Francesco Cosentino, Harald Oberhauser, Alessandro Abate

A Fair Classifier Using Kernel Density Estimation

Jaewoong Cho, Gyeongjo Hwang, Changho Suh

The Autoencoding Variational Autoencoder

Taylan Cemgil, Sumedh Ghaisas, Krishnamurthy Dvijotham, Sven Gowal, Pushmeet Kohli

From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering

Ines Chami, Albert Gu, Vaggos Chatziafratis, Christopher Re

Adaptive Experimental Design with Temporal Interference: A Maximum Likelihood Approach

Peter W. Glynn, Ramesh Johari, Mohammad Rasouli

Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping

Eduard Gorbunov, Marina Danilova, Alexander Gasnikov

Learning to Select Best Forecast Tasks for Clinical Outcome Prediction

Yuan Xue, Nan Du, Anne Mottram, Martin Seneviratne, Andrew M Dai

Online learning with dynamics: A minimax perspective

Kush Bhatia, Karthik Sridharan

Online Adaptation for Consistent Mesh Reconstruction in the Wild

Xueting Li, Sifei Liu, Shalini De Mello, Kihwan Kim, Xiaolong Wang

Learning Feature Sparse Principal Subspace

Lai Tian, Feiping Nie, Rong Wang, Xuelong Li

A Biologically Plausible Neural Network for Slow Feature Analysis

David Lipshutz, Charles Windolf, Siavash Golkar, Dmitri B. Chklovskii

Adversarial Training is a Form of Data-dependent Operator Norm Regularization

Kevin Roth, Yannic Kilcher, Thomas Hofmann

See, Hear, Explore: Curiosity via Audio-Visual Association

Victoria Dean, Shubham Tulsiani, Abhinav Gupta

Bayesian Pseudocoresets

Dionysis Manousakas, Zuheng Xu, Cecilia Mascolo, Trevor Campbell

Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks

Randall Balestriero, Sebastien PARIS, Richard Baraniuk

Deep Evidential Regression

Alexander Amini, Wilko Schwarting, Ava Soleimany, Daniela Rus

All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimation

jean barbier, Nicolas Macris, Cynthia Rush

Understanding and Exploring the Network with Stochastic Architectures

Zhijie Deng, Yinpeng Dong, Shifeng Zhang, Jun Zhu

Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs

Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao

Coresets via Bilevel Optimization for Continual Learning and Streaming

Zalán Borsos, Mojmir Mutny, Andreas Krause

Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations

Joshua Glaser, Matthew Whiteway, John P. Cunningham, Liam Paninski, Scott Linderman

Efficient Clustering Based On A Unified View Of K-means And Ratio-cut

Shenfei Pei, Feiping Nie, Rong Wang, Xuelong Li

A Variational Approach for Learning from Positive and Unlabeled Data

Hui Chen, Fangqing Liu, Yin Wang, Liyue Zhao, Hao Wu

STEER : Simple Temporal Regularization For Neural ODE

Arnab Ghosh, Harkirat Behl, Emilien Dupont, Philip Torr, Vinay Namboodiri

When Do Neural Networks Outperform Kernel Methods?

Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari

AdaTune: Adaptive Tensor Program Compilation Made Efficient

Menghao Li, Minjia Zhang, Chi Wang, Mingqin Li

Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis

Shaocong Ma, Yi Zhou, Shaofeng Zou

Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement

Ben Eysenbach, XINYANG GENG, Sergey Levine, Ruslan Salakhutdinov

Entropic Causal Inference: Identifiability and Finite Sample Results

Spencer Compton, Murat Kocaoglu, Kristjan Greenewald, Dmitriy Katz

Task-Oriented Feature Distillation

Linfeng Zhang, Yukang Shi, Zuoqiang Shi, Kaisheng Ma, Chenglong Bao

Storage Efficient and Dynamic Flexible Runtime Channel Pruning via Deep Reinforcement Learning

Jianda Chen, Shangyu Chen, Sinno Jialin Pan

Implicit Rank-Minimizing Autoencoder

Li Jing, Jure Zbontar, Yann LeCun

Learning Sparse Prototypes for Text Generation

Junxian He, Taylor Berg-Kirkpatrick, Graham Neubig

A Single Recipe for Online Submodular Maximization with Adversarial or Stochastic Constraints

Omid Sadeghi, Prasanna Raut, Maryam Fazel

Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning

Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S Meel, N. V. Vinodchandran

Recovery of sparse linear classifiers from mixture of responses

Venkata Gandikota, Arya Mazumdar, Soumyabrata Pal

Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity Learning

Huan Fu, Shunming Li, Rongfei Jia, Mingming Gong, Binqiang Zhao

Efficient Generation of Structured Objects with Constrained Adversarial Networks

Luca Di Liello, Pierfrancesco Ardino, Jacopo Gobbi, Paolo Morettin, Stefano Teso

Black-Box Optimization with Local Generative Surrogates

Sergey Shirobokov, Vladislav Belavin, Michael Kagan, Andrei Ustyuzhanin, Atilim Gunes Baydin

Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad Samples

Samarth Sinha, Zhengli Zhao, Anirudh Goyal ALIAS PARTH GOYAL, Colin A Raffel, Augustus Odena

Reducing Adversarially Robust Learning to Non-Robust PAC Learning

Omar Montasser, Steve Hanneke, Nati Srebro

Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks

Jy-yong Sohn, Dong-Jun Han, Beongjun Choi, Jaekyun Moon

STLnet: Signal Temporal Logic Enforced Multivariate Recurrent Neural Networks

Meiyi Ma, Ji Gao, Lu Feng, John Stankovic

The Strong Screening Rule for SLOPE

Johan Larsson, Malgorzata Bogdan, Jonas Wallin

Assisted Learning: A Framework for Multi-Organization Learning

Xun Xian, Xinran Wang, Jie Ding, Reza Ghanadan

Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning

Jaehyung Kim, Youngbum Hur, Sejun Park, Eunho Yang, Sung Ju Hwang

Scalable Graph Neural Networks via Bidirectional Propagation

Ming Chen, Zhewei Wei, Bolin Ding, Yaliang Li, Ye Yuan

Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate

Zhiyuan Li, Kaifeng Lyu, Sanjeev Arora

Learning the Linear Quadratic Regulator from Nonlinear Observations

Zakaria Mhammedi, Dylan J Foster, Max Simchowitz, Dipendra Misra, Wen Sun

Leveraging Predictions in Smoothed Online Convex Optimization via Gradient-based Algorithms

Yingying Li, Na Li

KFC: A Scalable Approximation Algorithm for k−center Fair Clustering

Elfarouk Harb, Ho Shan Lam

Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks

Yimeng Min, Frederik Wenkel, Guy Wolf

Planning with General Objective Functions: Going Beyond Total Rewards

Ruosong Wang, Peilin Zhong, Simon S Du, Ruslan Salakhutdinov, Lin Yang

CoinPress: Practical Private Mean and Covariance Estimation

Sourav Biswas, Yihe Dong, Gautam Kamath, Jonathan Ullman

MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler

Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian

Fast geometric learning with symbolic matrices

Jean Feydy, Alexis Glaunès, Benjamin Charlier, Michael Bronstein

Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness

Long Zhao, Ting Liu, Xi Peng, Dimitris Metaxas

Spike and slab variational Bayes for high dimensional logistic regression

Kolyan Ray, Botond Szabo, Gabriel Clara

Kernel Methods Through the Roof: Handling Billions of Points Efficiently

Giacomo Meanti, Luigi Carratino, Lorenzo Rosasco, Alessandro Rudi

Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting

Jorge Mendez, Boyu Wang, Eric Eaton

Organizing recurrent network dynamics by task-computation to enable continual learning

Lea Duncker, Laura Driscoll, Krishna V. Shenoy, Maneesh Sahani, David Sussillo

Meta-Consolidation for Continual Learning

Joseph K J, Vineeth N Balasubramanian

Adversarial Attacks on Linear Contextual Bandits

Evrard Garcelon, Baptiste Roziere, Laurent Meunier, Jean Tarbouriech, Olivier Teytaud

Point process models for sequence detection in high-dimensional neural spike trains

Alex Williams, Anthony Degleris, Yixin Wang, Scott Linderman

Knowledge Augmented Deep Neural Networks for Joint Facial Expression and Action Unit Recognition

Zijun Cui, Tengfei Song, Yuru Wang, Qiang Ji

Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View Consistency

Fang Zhao, Shengcai Liao, Kaihao Zhang, Ling Shao

Prediction with Corrupted Expert Advice

Idan Amir, Idan Attias, Tomer Koren, Yishay Mansour, Roi Livni

Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities

Chaobing Song, Zhengyuan Zhou, Yichao Zhou, Yong Jiang, Yi Ma