ICML 2020

1,084 papers

Do GANs always have Nash equilibria?

Farzan Farnia, Asuman Ozdaglar

Stochastic Regret Minimization in Extensive-Form Games

Gabriele Farina, Christian Kroer, Tuomas Sandholm

Online mirror descent and dual averaging: keeping pace in the dynamic case

Huang Fang, Nick Harvey, Victor Portella, Michael Friedlander

On hyperparameter tuning in general clustering problemsm

Xinjie Fan, Yuguang Yue, Purnamrita Sarkar, Y. X. Rachel Wang

Spectral Graph Matching and Regularized Quadratic Relaxations: Algorithm and Theory

Zhou Fan, Cheng Mao, Yihong Wu, Jiaming Xu

Optimal Sequential Maximization: One Interview is Enough!

Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati

Latent Bernoulli Autoencoder

Jiri Fajtl, Vasileios Argyriou, Dorothy Monekosso, Paolo Remagnino

Faster Graph Embeddings via Coarsening

Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang

Rigging the Lottery: Making All Tickets Winners

Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen

Distributed Online Optimization over a Heterogeneous Network with Any-Batch Mirror Descent

Nima Eshraghi, Ben Liang

Identifying Statistical Bias in Dataset Replication

Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt

Continuous Time Bayesian Networks with Clocks

Nicolai Engelmann, Dominik Linzner, Heinz Koeppl

Parallel Algorithm for Non-Monotone DR-Submodular Maximization

Alina Ene, Huy Nguyen

Generalization Error of Generalized Linear Models in High Dimensions

Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson Fletcher

Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks

Ahmed Taha Elthakeb, Prannoy Pilligundla, Fatemeh Mireshghallah, Alexander Cloninger, Hadi Esmaeilzadeh

Revisiting Spatial Invariance with Low-Rank Local Connectivity

Gamaleldin Elsayed, Prajit Ramachandran, Jonathon Shlens, Simon Kornblith

Decision Trees for Decision-Making under the Predict-then-Optimize Framework

Adam N. Elmachtoub, Jason Cheuk Nam Liang, Ryan Mcnellis

Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location

Rasheed El-Bouri, David Eyre, Peter Watkinson, Tingting Zhu, David Clifton

Training Linear Neural Networks: Non-Local Convergence and Complexity Results

Armin eftekhari

Estimating Q(s,s’) with Deep Deterministic Dynamics Gradients

Ashley Edwards, Himanshu Sahni, Rosanne Liu, Jane Hung, Ankit Jain

Self-Concordant Analysis of Frank-Wolfe Algorithms

Pavel Dvurechensky, Petr Ostroukhov, Kamil Safin, Shimrit Shtern, Mathias Staudigl

Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing

Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu

Sparse Gaussian Processes with Spherical Harmonic Features

Vincent Dutordoir, Nicolas Durrande, James Hensman

Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors

Michael Dusenberry, Ghassen Jerfel, Yeming Wen, Yian Ma, Jasper Snoek

On Contrastive Learning for Likelihood-free Inference

Conor Durkan, Iain Murray, George Papamakarios

Equivariant Neural Rendering

Emilien Dupont, Miguel Bautista Martin, Alex Colburn, Aditya Sankar, Josh Susskind

Optimization Theory for ReLU Neural Networks Trained with Normalization Layers

Yonatan Dukler, Quanquan Gu, Guido Montúfar

Kernel Methods for Cooperative Multi-Agent Contextual Bandits

Abhimanyu Dubey, Alex ‘Sandy’ Pentland

Cooperative Multi-Agent Bandits with Heavy Tails

Abhimanyu Dubey, Alex ‘Sandy’ Pentland

Familywise Error Rate Control by Interactive Unmasking

Boyan Duan, Aaditya Ramdas, Larry Wasserman

Online Bayesian Moment Matching based SAT Solver Heuristics

Haonan Duan, Saeed Nejati, George Trimponias, Pascal Poupart, Vijay Ganesh

Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation

Yaqi Duan, Zeyu Jia, Mengdi Wang

NGBoost: Natural Gradient Boosting for Probabilistic Prediction

Tony Duan, Avati Anand, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu

Reserve Pricing in Repeated Second-Price Auctions with Strategic Bidders

Alexey Drutsa

Optimal Non-parametric Learning in Repeated Contextual Auctions with Strategic Buyer

Alexey Drutsa

The Complexity of Finding Stationary Points with Stochastic Gradient Descent

Yoel Drori, Ohad Shamir

Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms

Chaosheng Dong, Bo Zeng

Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems

Zhe Dong, Bryan Seybold, Kevin Murphy, Hung Bui

On the Expressivity of Neural Networks for Deep Reinforcement Learning

Kefan Dong, Yuping Luo, Tianhe Yu, Chelsea Finn, Tengyu Ma

Towards Adaptive Residual Network Training: A Neural-ODE Perspective

Chengyu Dong, Liyuan Liu, Zichao Li, Jingbo Shang

Multinomial Logit Bandit with Low Switching Cost

Kefan Dong, Yingkai Li, Qin Zhang, Yuan Zhou

Optimal Differential Privacy Composition for Exponential Mechanisms

Jinshuo Dong, David Durfee, Ryan Rogers

Provable Smoothness Guarantees for Black-Box Variational Inference

Justin Domke

Inexact Tensor Methods with Dynamic Accuracies

Nikita Doikov, Yurii Nesterov

Growing Adaptive Multi-hyperplane Machines

Nemanja Djuric, Zhuang Wang, Slobodan Vucetic

Layered Sampling for Robust Optimization Problems

Hu Ding, Zixiu Wang

Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features

Liang Ding, Rui Tuo, Shahin Shahrampour

Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence

Lijun Ding, Yingjie Fei, Qiantong Xu, Chengrun Yang

Enhancing Simple Models by Exploiting What They Already Know

Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss

Margin-aware Adversarial Domain Adaptation with Optimal Transport

Sofien Dhouib, Ievgen Redko, Carole Lartizien

A Swiss Army Knife for Minimax Optimal Transport

Sofien Dhouib, Ievgen Redko, Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban

Robust Pricing in Dynamic Mechanism Design

Yuan Deng, Sebastien Lahaie, Vahab Mirrokni

Towards Understanding the Dynamics of the First-Order Adversaries

Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie Su

Non-convex Learning via Replica Exchange Stochastic Gradient MCMC

Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin

Interpreting Robust Optimization via Adversarial Influence Functions

Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang

Randomly Projected Additive Gaussian Processes for Regression

Ian Delbridge, David Bindel, Andrew Gordon Wilson

Structure Adaptive Algorithms for Stochastic Bandits

Rémy Degenne, Han Shao, Wouter Koolen

Gamification of Pure Exploration for Linear Bandits

Rémy Degenne, Pierre Menard, Xuedong Shang, Michal Valko

An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm

Chris Decarolis, Mukul Ram, Seyed Esmaeili, Yu-Xiang Wang, Furong Huang

Representing Unordered Data Using Complex-Weighted Multiset Automata

Justin DeBenedetto, David Chiang

Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction

Filipe de Avila Belbute-Peres, Thomas Economon, Zico Kolter

Low-Variance and Zero-Variance Baselines for Extensive-Form Games

Trevor Davis, Martin Schmid, Michael Bowling

Probing Emergent Semantics in Predictive Agents via Question Answering

Abhishek Das, Federico Carnevale, Hamza Merzic, Laura Rimell, Rosalia Schneider

Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors

Yehuda Dar, Paul Mayer, Lorenzo Luzi, Richard Baraniuk

Adversarial Attacks on Probabilistic Autoregressive Forecasting Models

Raphaël Dang-Nhu, Gagandeep Singh, Pavol Bielik, Martin Vechev

Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification

Chen Dan, Yuting Wei, Pradeep Ravikumar

Goodness-of-Fit Tests for Inhomogeneous Random Graphs

Soham Dan, Bhaswar B. Bhattacharya

Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting

Niccolò Dalmasso, Rafael Izbicki, Ann Lee

The Usual Suspects? Reassessing Blame for VAE Posterior Collapse

Bin Dai, Ziyu Wang, David Wipf

Scalable Deep Generative Modeling for Sparse Graphs

Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans

R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games

Zhongxiang Dai, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet, Teck-Hua Ho

Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime

Stéphane D’Ascoli, Maria Refinetti, Giulio Biroli, Florent Krzakala

Supervised Quantile Normalization for Low Rank Matrix Factorization

Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed, Jean-philippe Vert

Momentum Improves Normalized SGD

Ashok Cutkosky, Harsh Mehta

Parameter-free, Dynamic, and Strongly-Adaptive Online Learning

Ashok Cutkosky

Flexible and Efficient Long-Range Planning Through Curious Exploration

Aidan Curtis, Minjian Xin, Dilip Arumugam, Kevin Feigelis, Daniel Yamins

Privately detecting changes in unknown distributions

Rachel Cummings, Sara Krehbiel, Yuliia Lut, Wanrong Zhang

Real-Time Optimisation for Online Learning in Auctions

Lorenzo Croissant, Marc Abeille, Clément Calauzènes

Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

Francesco Croce, Matthias Hein

Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack

Francesco Croce, Matthias Hein

Causal Modeling for Fairness In Dynamical Systems

Elliot Creager, David Madras, Toniann Pitassi, Richard Zemel

DINO: Distributed Newton-Type Optimization Method

Rixon Crane, Fred Roosta

Learnable Group Transform For Time-Series

Romain Cosentino, Behnaam Aazhang

Online Learning with Dependent Stochastic Feedback Graphs

Corinna Cortes, Giulia DeSalvo, Claudio Gentile, Mehryar Mohri, Ningshan Zhang

Adaptive Region-Based Active Learning

Corinna Cortes, Giulia DeSalvo, Claudio Gentile, Mehryar Mohri, Ningshan Zhang

Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows

Rob Cornish, Anthony Caterini, George Deligiannidis, Arnaud Doucet

Learning Opinions in Social Networks

Vincent Conitzer, Debmalya Panigrahi, Hanrui Zhang

Boosting Frank-Wolfe by Chasing Gradients

Cyrille Combettes, Sebastian Pokutta

Word-Level Speech Recognition With a Letter to Word Encoder

Ronan Collobert, Awni Hannun, Gabriel Synnaeve

Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data

Benjamin Coleman, Richard Baraniuk, Anshumali Shrivastava

On Efficient Low Distortion Ultrametric Embedding

Vincent Cohen-Addad, Karthik C. S., Guillaume Lagarde

Healing Products of Gaussian Process Experts

Samuel Cohen, Rendani Mbuvha, Tshilidzi Marwala, Marc Deisenroth

Composable Sketches for Functions of Frequencies: Beyond the Worst Case

Edith Cohen, Ofir Geri, Rasmus Pagh

Leveraging Procedural Generation to Benchmark Reinforcement Learning

Karl Cobbe, Chris Hesse, Jacob Hilton, John Schulman

Model Fusion with Kullback-Leibler Divergence

Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon

Deep Divergence Learning

Hatice Kubra Cilingir, Rachel Manzelli, Brian Kulis

Teaching with Limited Information on the Learner’s Behaviour

Ferdinando Cicalese, Sergio Filho, Eduardo Laber, Marco Molinaro

Feature-map-level Online Adversarial Knowledge Distillation

Inseop Chung, Seonguk Park, Jangho Kim, Nojun Kwak

Scalable and Efficient Comparison-based Search without Features

Daniyar Chumbalov, Lucas Maystre, Matthias Grossglauser

Estimating Generalization under Distribution Shifts via Domain-Invariant Representations

Ching-Yao Chuang, Antonio Torralba, Stefanie Jegelka