NeurIPS 2020

1,898 papers

Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization

Xuefeng GAO, Mert Gurbuzbalaban, Lingjiong Zhu

Learning outside the Black-Box: The pursuit of interpretable models

Jonathan Crabbe, Yao Zhang, William Zame, Mihaela van der Schaar

Robustness of Community Detection to Random Geometric Perturbations

Sandrine Peche, Vianney Perchet

On Reward-Free Reinforcement Learning with Linear Function Approximation

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

Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

LEI BAI, Lina Yao, Can Li, Xianzhi Wang, Can Wang

Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies

Yuehua Zhu, Muli Yang, Cheng Deng, Wei Liu

Online Multitask Learning with Long-Term Memory

Mark Herbster, Stephen Pasteris, Lisa Tse

Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting

Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu

Continuous Regularized Wasserstein Barycenters

Lingxiao Li, Aude Genevay, Mikhail Yurochkin, Justin M Solomon

Axioms for Learning from Pairwise Comparisons

Ritesh Noothigattu, Dominik Peters, Ariel D Procaccia

Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization

Chong You, Zhihui Zhu, Qing Qu, Yi Ma

SOLOv2: Dynamic and Fast Instance Segmentation

Xinlong Wang, Rufeng Zhang, Tao Kong, Lei Li, Chunhua Shen

Diversity-Guided Multi-Objective Bayesian Optimization With Batch Evaluations

Mina Konakovic Lukovic, Yunsheng Tian, Wojciech Matusik

ARMA Nets: Expanding Receptive Field for Dense Prediction

Jiahao Su, Shiqi Wang, Furong Huang

Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis

Kavi Gupta, Peter Ebert Christensen, Xinyun Chen, Dawn Song

The All-or-Nothing Phenomenon in Sparse Tensor PCA

Jonathan Niles-Weed, Ilias Zadik

Online Meta-Critic Learning for Off-Policy Actor-Critic Methods

Wei Zhou, Yiying Li, Yongxin Yang, Huaimin Wang, Timothy Hospedales

A convex optimization formulation for multivariate regression

Yunzhang Zhu

Learning to Mutate with Hypergradient Guided Population

Zhiqiang Tao, Yaliang Li, Bolin Ding, Ce Zhang, Jingren Zhou

Pruning Filter in Filter

Fanxu Meng, Hao Cheng, Ke Li, Huixiang Luo, Xiaowei Guo

A Finite-Time Analysis of Two Time-Scale Actor-Critic Methods

Yue Frank Wu, Weitong ZHANG, Pan Xu, Quanquan Gu

Learning Invariances in Neural Networks from Training Data

Gregory Benton, Marc Finzi, Pavel Izmailov, Andrew G Wilson

Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targets

Avetik Karagulyan, Arnak Dalalyan

A mathematical theory of cooperative communication

Pei Wang, Junqi Wang, Pushpi Paranamana, Patrick Shafto

Continuous Meta-Learning without Tasks

James Harrison, Apoorva Sharma, Chelsea Finn, Marco Pavone

CO-Optimal Transport

Vayer Titouan, Ievgen Redko, Rémi Flamary, Nicolas Courty

Neural Manifold Ordinary Differential Equations

Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang

Unsupervised Joint k-node Graph Representations with Compositional Energy-Based Models

Leonardo Cotta, Carlos H. C. Teixeira, Ananthram Swami, Bruno Ribeiro

SGD with shuffling: optimal rates without component convexity and large epoch requirements

Kwangjun Ahn, Chulhee Yun, Suvrit Sra

Applications of Common Entropy for Causal Inference

Murat Kocaoglu, Sanjay Shakkottai, Alexandros G Dimakis, Constantine Caramanis, Sriram Vishwanath

Reasoning about Uncertainties in Discrete-Time Dynamical Systems using Polynomial Forms.

Sriram Sankaranarayanan, Yi Chou, Eric Goubault, Sylvie Putot

Dense Correspondences between Human Bodies via Learning Transformation Synchronization on Graphs

Xiangru Huang, Haitao Yang, Etienne Vouga, Qixing Huang

ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool

Gellert Weisz, András György, Wei-I Lin, Devon Graham, Kevin Leyton-brown

Mitigating Forgetting in Online Continual Learning via Instance-Aware Parameterization

Hung-Jen Chen, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun

Cooperative Heterogeneous Deep Reinforcement Learning

Han Zheng, Pengfei Wei, Jing Jiang, Guodong Long, Qinghua Lu

Real World Games Look Like Spinning Tops

Wojciech M. Czarnecki, Gauthier Gidel, Brendan Tracey, Karl Tuyls, Shayegan Omidshafiei

Discovering Symbolic Models from Deep Learning with Inductive Biases

Miles Cranmer, Alvaro Sanchez Gonzalez, Peter Battaglia, Rui Xu, Kyle Cranmer

Towards Neural Programming Interfaces

Zachary Brown, Nathaniel Robinson, David Wingate, Nancy Fulda

Disentangling by Subspace Diffusion

David Pfau, Irina Higgins, Alex Botev, Sébastien Racanière

The Dilemma of TriHard Loss and an Element-Weighted TriHard Loss for Person Re-Identification

Yihao Lv, Youzhi Gu, Liu Xinggao

Unfolding recurrence by Green’s functions for optimized reservoir computing

Sandra Nestler, Christian Keup, David Dahmen, Matthieu Gilson, Holger Rauhut

f-Divergence Variational Inference

Neng Wan, Dapeng Li, NAIRA HOVAKIMYAN

Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization

Abhinav Agrawal, Daniel R. Sheldon, Justin Domke

Dual-Resolution Correspondence Networks

Xinghui Li, Kai Han, Shuda Li, Victor Prisacariu

Statistical Optimal Transport posed as Learning Kernel Embedding

Saketha Nath Jagarlapudi, Pratik Kumar Jawanpuria

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors

Karl Pertsch, Oleh Rybkin, Frederik Ebert, Shenghao Zhou, Dinesh Jayaraman

Random Reshuffling: Simple Analysis with Vast Improvements

Konstantin Mishchenko, Ahmed Khaled, Peter Richtarik

Neural Execution Engines: Learning to Execute Subroutines

Yujun Yan, Kevin Swersky, Danai Koutra, Parthasarathy Ranganathan, Milad Hashemi

Big Bird: Transformers for Longer Sequences

Manzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti

Succinct and Robust Multi-Agent Communication With Temporal Message Control

Sai Qian Zhang, Qi Zhang, Jieyu Lin

Continuous Surface Embeddings

Natalia Neverova, David Novotny, Marc Szafraniec, Vasil Khalidov, Patrick Labatut

Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning

Weishi Shi, Xujiang Zhao, Feng Chen, Qi Yu

Co-Tuning for Transfer Learning

Kaichao You, Zhi Kou, Mingsheng Long, Jianmin Wang

Online Non-Convex Optimization with Imperfect Feedback

Amélie Heliou, Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier

Understanding Global Feature Contributions With Additive Importance Measures

Ian Covert, Scott M Lundberg, Su-in Lee

Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits

Jack Parker-Holder, Vu Nguyen, Stephen J. Roberts

Functional Regularization for Representation Learning: A Unified Theoretical Perspective

Siddhant Garg, Yingyu Liang

Directional convergence and alignment in deep learning

Ziwei Ji, Matus J. Telgarsky

Calibrated Reliable Regression using Maximum Mean Discrepancy

Peng Cui, Wenbo Hu, Jun Zhu

Compositional Explanations of Neurons

Jesse Mu, Jacob Andreas

Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights

Theofanis Karaletsos, Thang D Bui

CLEARER: Multi-Scale Neural Architecture Search for Image Restoration

Yuanbiao Gou, Boyun Li, Zitao Liu, Songfan Yang, Xi Peng

The Surprising Simplicity of the Early-Time Learning Dynamics of Neural Networks

Wei Hu, Lechao Xiao, Ben Adlam, Jeffrey Pennington

Adversarial Sparse Transformer for Time Series Forecasting

Sifan Wu, Xi Xiao, Qianggang Ding, Peilin Zhao, Ying Wei

Mixed Hamiltonian Monte Carlo for Mixed Discrete and Continuous Variables

Guangyao Zhou

Contrastive Learning with Adversarial Examples

Chih-Hui Ho, Nuno Nvasconcelos

High-Throughput Synchronous Deep RL

Iou-Jen Liu, Raymond Yeh, Alexander Schwing

Combining Deep Reinforcement Learning and Search for Imperfect-Information Games

Noam Brown, Anton Bakhtin, Adam Lerer, Qucheng Gong

Identifying Mislabeled Data using the Area Under the Margin Ranking

Geoff Pleiss, Tianyi Zhang, Ethan Elenberg, Kilian Q. Weinberger

Unbalanced Sobolev Descent

Youssef Mroueh, Mattia Rigotti

HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis

Jungil Kong, Jaehyeon Kim, Jaekyoung Bae

Design Space for Graph Neural Networks

Jiaxuan You, Zhitao Ying, Jure Leskovec

SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection

Xiaoya Li, Yuxian Meng, Mingxin Zhou, Qinghong Han, Fei Wu

CHIP: A Hawkes Process Model for Continuous-time Networks with Scalable and Consistent Estimation

Makan Arastuie, Subhadeep Paul, Kevin Xu

A Stochastic Path Integral Differential EstimatoR Expectation Maximization Algorithm

Gersende Fort, Eric Moulines, Hoi-To Wai

CryptoNAS: Private Inference on a ReLU Budget

Zahra Ghodsi, Akshaj Kumar Veldanda, Brandon Reagen, Siddharth Garg

Dynamic allocation of limited memory resources in reinforcement learning

Nisheet Patel, Luigi Acerbi, Alexandre Pouget

Inverting Gradients - How easy is it to break privacy in federated learning?

Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller

Bayes Consistency vs. H-Consistency: The Interplay between Surrogate Loss Functions and the Scoring Function Class

Mingyuan Zhang, Shivani Agarwal

Conformal Symplectic and Relativistic Optimization

Guilherme Franca, Jeremias Sulam, Daniel Robinson, René Vidal

Fast Adaptive Non-Monotone Submodular Maximization Subject to a Knapsack Constraint

Georgios Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Rebecca Reiffenhäuser

Lipschitz-Certifiable Training with a Tight Outer Bound

Sungyoon Lee, Jaewook Lee, Saerom Park

Zap Q-Learning With Nonlinear Function Approximation

Shuhang Chen, Adithya M Devraj, Fan Lu, Ana Busic, Sean Meyn

Reinforcement Learning with Feedback Graphs

Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

MPNet: Masked and Permuted Pre-training for Language Understanding

Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-yan Liu

Few-shot Visual Reasoning with Meta-Analogical Contrastive Learning

Youngsung Kim, Jinwoo Shin, Eunho Yang, Sung Ju Hwang

PAC-Bayes Analysis Beyond the Usual Bounds

Omar Rivasplata, Ilja Kuzborskij, Csaba Szepesvári, John Shawe-Taylor

Ratio Trace Formulation of Wasserstein Discriminant Analysis

Hexuan Liu, Yunfeng Cai, You-Lin Chen, Ping Li

Linear Dynamical Systems as a Core Computational Primitive

Shiva Kaul

Comprehensive Attention Self-Distillation for Weakly-Supervised Object Detection

Zeyi Huang, Yang Zou, B. V. K. Vijaya Kumar, Dong Huang

Reservoir Computing meets Recurrent Kernels and Structured Transforms

Jonathan Dong, Ruben Ohana, Mushegh Rafayelyan, Florent Krzakala

A Feasible Level Proximal Point Method for Nonconvex Sparse Constrained Optimization

Digvijay Boob, Qi Deng, Guanghui Lan, Yilin Wang

Hierarchical Patch VAE-GAN: Generating Diverse Videos from a Single Sample

Shir Gur, Sagie Benaim, Lior Wolf

Decisions, Counterfactual Explanations and Strategic Behavior

Stratis Tsirtsis, Manuel Gomez Rodriguez

RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning

Riccardo Del Chiaro, Bartłomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer

Probably Approximately Correct Constrained Learning

Luiz Chamon, Alejandro Ribeiro

AViD Dataset: Anonymized Videos from Diverse Countries

AJ Piergiovanni, Michael Ryoo

On the Equivalence between Online and Private Learnability beyond Binary Classification

Young Jung, Baekjin Kim, Ambuj Tewari

Interpolation Technique to Speed Up Gradients Propagation in Neural ODEs

Talgat Daulbaev, Alexandr Katrutsa, Larisa Markeeva, Julia Gusak, Andrzej Cichocki

Predictive coding in balanced neural networks with noise, chaos and delays

Jonathan Kadmon, Jonathan Timcheck, Surya Ganguli