ICML 2020

1,084 papers

Semismooth Newton Algorithm for Efficient Projections onto ℓ_1, ∞-norm Ball

Dejun Chu, Changshui Zhang, Shiliang Sun, Qing Tao

Distance Metric Learning with Joint Representation Diversification

Xu Chu, Yang Lin, Yasha Wang, Xiting Wang, Hailong Yu

Online Continual Learning from Imbalanced Data

Aristotelis Chrysakis, Marie-Francine Moens

Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models

Amrita Roy Chowdhury, Theodoros Rekatsinas, Somesh Jha

Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels

Yu-Ting Chou, Gang Niu, Hsuan-tien Lin, Masashi Sugiyama

Stochastic Flows and Geometric Optimization on the Orthogonal Group

Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret

k-means++: few more steps yield constant approximation

Davin Choo, Christoph Grunau, Julian Portmann, Vaclav Rozhon

Encoding Musical Style with Transformer Autoencoders

Kristy Choi, Curtis Hawthorne, Ian Simon, Monica Dinculescu, Jesse Engel

Fair Generative Modeling via Weak Supervision

Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon

How to Solve Fair k-Center in Massive Data Models

Ashish Chiplunkar, Sagar Kale, Sivaramakrishnan Natarajan Ramamoorthy

On Coresets for Regularized Regression

Rachit Chhaya, Anirban Dasgupta, Supratim Shit

Streaming Coresets for Symmetric Tensor Factorization

Rachit Chhaya, Jayesh Choudhari, Anirban Dasgupta, Supratim Shit

Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism

Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu

Convergence Rates of Variational Inference in Sparse Deep Learning

Badr-Eddine Chérief-Abdellatif

Representation Learning via Adversarially-Contrastive Optimal Transport

Anoop Cherian, Shuchin Aeron

Stochastic Gradient and Langevin Processes

Xiang Cheng, Dong Yin, Peter Bartlett, Michael Jordan

Mutual Transfer Learning for Massive Data

Ching-Wei Cheng, Xingye Qiao, Guang Cheng

Learning with Bounded Instance and Label-dependent Label Noise

Jiacheng Cheng, Tongliang Liu, Kotagiri Ramamohanarao, Dacheng Tao

CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information

Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan

High-dimensional Robust Mean Estimation via Gradient Descent

Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi

(Locally) Differentially Private Combinatorial Semi-Bandits

Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen

Automated Synthetic-to-Real Generalization

Wuyang Chen, Zhiding Yu, Zhangyang Wang, Animashree Anandkumar

On Breaking Deep Generative Model-based Defenses and Beyond

Yanzhi Chen, Renjie Xie, Zhanxing Zhu

Simple and Deep Graph Convolutional Networks

Ming Chen, Zhewei Wei, zengfeng Huang, Bolin Ding, Yaliang Li

Optimization from Structured Samples for Coverage Functions

Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang

Negative Sampling in Semi-Supervised learning

John Chen, Vatsal Shah, Anastasios Kyrillidis

Generative Pretraining From Pixels

Mark Chen, Alec Radford, Rewon Child, Jeffrey Wu, Heewoo Jun

An Accelerated DFO Algorithm for Finite-sum Convex Functions

Yuwen Chen, Antonio Orvieto, Aurelien Lucchi

More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models

Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi

VFlow: More Expressive Generative Flows with Variational Data Augmentation

Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, TIAN TIAN

Estimating the Error of Randomized Newton Methods: A Bootstrap Approach

Jessie X.T. Chen, Miles Lopes

Angular Visual Hardness

Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava

On Efficient Constructions of Checkpoints

Yu Chen, Zhenming Liu, Bin Ren, Xin Jin

Differentiable Product Quantization for End-to-End Embedding Compression

Ting Chen, Lala Li, Yizhou Sun

Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search

Binghong Chen, Chengtao Li, Hanjun Dai, Le Song

A Simple Framework for Contrastive Learning of Visual Representations

Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey Hinton

Learning Flat Latent Manifolds with VAEs

Nutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick van der Smagt

Convolutional Kernel Networks for Graph-Structured Data

Dexiong Chen, Laurent Jacob, Julien Mairal

Mapping natural-language problems to formal-language solutions using structured neural representations

Kezhen Chen, Qiuyuan Huang, Hamid Palangi, Paul Smolensky, Ken Forbus

Stabilizing Differentiable Architecture Search via Perturbation-based Regularization

Xiangning Chen, Cho-jui Hsieh

Graph Optimal Transport for Cross-Domain Alignment

Liqun Chen, Zhe Gan, Yu Cheng, Linjie Li, Lawrence Carin

Combinatorial Pure Exploration for Dueling Bandit

Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao

Learning To Stop While Learning To Predict

Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song

Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training

Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gong

Deep Reasoning Networks for Unsupervised Pattern De-mixing with Constraint Reasoning

Di Chen, Yiwei Bai, Wenting Zhao, Sebastian Ament, John Gregoire

Uncertainty-Aware Lookahead Factor Models for Quantitative Investing

Lakshay Chauhan, John Alberg, Zachary Lipton

Explainable and Discourse Topic-aware Neural Language Understanding

Yatin Chaudhary, Hinrich Schuetze, Pankaj Gupta

Better depth-width trade-offs for neural networks through the lens of dynamical systems

Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas

Circuit-Based Intrinsic Methods to Detect Overfitting

Satrajit Chatterjee, Alan Mishchenko

Invariant Rationalization

Shiyu Chang, Yang Zhang, Mo Yu, Tommi Jaakkola

Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions

Michael Chang, Sid Kaushik, S. Matthew Weinberg, Tom Griffiths, Sergey Levine

Learning to Simulate and Design for Structural Engineering

Kai-Hung Chang, Chin-Yi Cheng

Optimizing for the Future in Non-Stationary MDPs

Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan

Imputer: Sequence Modelling via Imputation and Dynamic Programming

William Chan, Chitwan Saharia, Geoffrey Hinton, Mohammad Norouzi, Navdeep Jaitly

Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift

Alex Chan, Ahmed Alaa, Zhaozhi Qian, Mihaela van der Schaar

Concise Explanations of Neural Networks using Adversarial Training

Prasad Chalasani, Jiefeng Chen, Amrita Roy Chowdhury, Xi Wu, Somesh Jha

Description Based Text Classification with Reinforcement Learning

Duo Chai, Wei Wu, Qinghong Han, Fei Wu, Jiwei Li

Meta-learning with Stochastic Linear Bandits

Leonardo Cella, Alessandro Lazaric, Massimiliano Pontil

Data preprocessing to mitigate bias: A maximum entropy based approach

L. Elisa Celis, Vijay Keswani, Nisheeth Vishnoi

Fully Parallel Hyperparameter Search: Reshaped Space-Filling

Marie-Liesse Cauwet, Camille Couprie, Julien Dehos, Pauline Luc, Jérémy Rapin

Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently

Asaf Cassel, Alon Cohen, Tomer Koren

Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills

Víctor Campos, Alexander Trott, Caiming Xiong, Richard Socher, Xavier Giró-i-Nieto

Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates

Jeff Calder, Brendan Cook, Matthew Thorpe, Dejan Slepcev

Near-linear time Gaussian process optimization with adaptive batching and resparsification

Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco

Provably Efficient Exploration in Policy Optimization

Qi Cai, Zhuoran Yang, Chi Jin, Zhaoran Wang

Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality

Changxiao Cai, H. Vincent Poor, Yuxin Chen

On Validation and Planning of An Optimal Decision Rule with Application in Healthcare Studies

Hengrui Cai, Wenbin Lu, Rui Song

Boosted Histogram Transform for Regression

Yuchao Cai, Hanyuan Hang, Hanfang Yang, Zhouchen Lin

Online Learned Continual Compression with Adaptive Quantization Modules

Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau

Structured Prediction with Partial Labelling through the Infimum Loss

Vivien Cabannnes, Alessandro Rudi, Francis Bach

DeBayes: a Bayesian Method for Debiasing Network Embeddings

Maarten Buyl, Tijl De Bie

Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models

Rares-Darius Buhai, Yoni Halpern, Yoon Kim, Andrej Risteski, David Sontag

Online Pricing with Offline Data: Phase Transition and Inverse Square Law

Jinzhi Bu, David Simchi-Levi, Yunzong Xu

Scalable Exact Inference in Multi-Output Gaussian Processes

Wessel Bruinsma, Eric Perim, William Tebbutt, Scott Hosking, Arno Solin

A Pairwise Fair and Community-preserving Approach to k-Center Clustering

Brian Brubach, Darshan Chakrabarti, John Dickerson, Samir Khuller, Aravind Srinivasan

Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences

Daniel Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum

TaskNorm: Rethinking Batch Normalization for Meta-Learning

John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard Turner

GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation

Marc Brockschmidt

The FAST Algorithm for Submodular Maximization

Adam Breuer, Eric Balkanski, Yaron Singer

Estimating the Number and Effect Sizes of Non-null Hypotheses

Jennifer Brennan, Ramya Korlakai Vinayak, Kevin Jamieson

All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference

Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan

Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension

Vladimir braverman, Robert Krauthgamer, Aditya Krishnan, Roi Sinoff

Calibration, Entropy Rates, and Memory in Language Models

Mark Braverman, Xinyi Chen, Sham Kakade, Karthik Narasimhan, Cyril Zhang

Adversarial Filters of Dataset Biases

Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew Peters

Preference Modeling with Context-Dependent Salient Features

Amanda Bower, Laura Balzano

Tightening Exploration in Upper Confidence Reinforcement Learning

Hippolyte Bourel, Odalric Maillard, Mohammad Sadegh Talebi

Latent Variable Modelling with Hyperbolic Normalizing Flows

Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, Will Hamilton

Small Data, Big Decisions: Model Selection in the Small-Data Regime

Jörg Bornschein, Francesco Visin, Simon Osindero

Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks

Blake Bordelon, Abdulkadir Canatar, Cengiz Pehlevan

Proper Network Interpretability Helps Adversarial Robustness in Classification

Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen

Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More

Aleksandar Bojchevski, Johannes Gasteiger, Stephan Günnemann

Lorentz Group Equivariant Neural Network for Particle Physics

Alexander Bogatskiy, Brandon Anderson, Jan Offermann, Marwah Roussi, David Miller

Deep Coordination Graphs

Wendelin Boehmer, Vitaly Kurin, Shimon Whiteson

Modulating Surrogates for Bayesian Optimization

Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill Campbell

Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization?

Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry

Fast Differentiable Sorting and Ranking

Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga

Provable guarantees for decision tree induction: the agnostic setting

Guy Blanc, Jane Lange, Li-Yang Tan

My Fair Bandit: Distributed Learning of Max-Min Fairness with Multi-player Bandits

Ilai Bistritz, Tavor Baharav, Amir Leshem, Nicholas Bambos

Tight Bounds on Minimax Regret under Logarithmic Loss via Self-Concordance

Blair Bilodeau, Dylan Foster, Daniel Roy

The Boomerang Sampler

Joris Bierkens, Sebastiano Grazzi, Kengo Kamatani, Gareth Roberts