ICML 2021

1,183 papers

Finding k in Latent $k-$ polytope

Chiranjib Bhattacharyya, Ravindran Kannan, Amit Kumar

Sample Complexity of Robust Linear Classification on Separated Data

Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri

Additive Error Guarantees for Weighted Low Rank Approximation

Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Maheshakya Wijewardena

Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries

Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal

Principal Bit Analysis: Autoencoding with Schur-Concave Loss

Sourbh Bhadane, Aaron B Wagner, Jayadev Acharya

Size-Invariant Graph Representations for Graph Classification Extrapolations

Beatrice Bevilacqua, Yangze Zhou, Bruno Ribeiro

Confidence Scores Make Instance-dependent Label-noise Learning Possible

Antonin Berthon, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama

Is Space-Time Attention All You Need for Video Understanding?

Gedas Bertasius, Heng Wang, Lorenzo Torresani

Learning from Biased Data: A Semi-Parametric Approach

Patrice Bertail, Stéphan Clémençon, Yannick Guyonvarch, Nathan Noiry

Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis

Jeroen Berrevoets, Ahmed Alaa, Zhaozhi Qian, James Jordon, Alexander E. S. Gimson

TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer

Berkay Berabi, Jingxuan He, Veselin Raychev, Martin Vechev

Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling

Gregory Benton, Wesley Maddox, Sanae Lotfi, Andrew Gordon Gordon Wilson

Policy Analysis using Synthetic Controls in Continuous-Time

Alexis Bellot, Mihaela van der Schaar

Directional Graph Networks

Dominique Beaini, Saro Passaro, Vincent Létourneau, Will Hamilton, Gabriele Corso

Generalized Doubly Reparameterized Gradient Estimators

Matthias Bauer, Andriy Mnih

On Limited-Memory Subsampling Strategies for Bandits

Dorian Baudry, Yoan Russac, Olivier Cappe

Optimal Thompson Sampling strategies for support-aware CVaR bandits

Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric Maillard

Beyond $log^2(T)$ regret for decentralized bandits in matching markets

Soumya Basu, Karthik Abinav Sankararaman, Abishek Sankararaman

Training Quantized Neural Networks to Global Optimality via Semidefinite Programming

Burak Bartan, Mert Pilanci

Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization

Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath

Approximating a Distribution Using Weight Queries

Nadav Barak, Sivan Sabato

Compositional Video Synthesis with Action Graphs

Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach, Gal Chechik

Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models

Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu

Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers

Yujia Bao, Shiyu Chang, Regina Barzilay

Regularized Online Allocation Problems: Fairness and Beyond

Santiago Balseiro, Haihao Lu, Vahab Mirrokni

Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment

Philip J Ball, Cong Lu, Jack Parker-Holder, Stephen Roberts

Instance Specific Approximations for Submodular Maximization

Eric Balkanski, Sharon Qian, Yaron Singer

Breaking the Limits of Message Passing Graph Neural Networks

Muhammet Balcilar, Pierre Héroux, Benoit Gaüzère, Pascal Vasseur, Sébastien Adam

GLSearch: Maximum Common Subgraph Detection via Learning to Search

Yunsheng Bai, Derek Xu, Yizhou Sun, Wei Wang

Principled Exploration via Optimistic Bootstrapping and Backward Induction

Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg

Don’t Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification

Yu Bai, Song Mei, Huan Wang, Caiming Xiong

Stabilizing Equilibrium Models by Jacobian Regularization

Shaojie Bai, Vladlen Koltun, Zico Kolter

How Important is the Train-Validation Split in Meta-Learning?

Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason Lee

Locally Adaptive Label Smoothing Improves Predictive Churn

Dara Bahri, Heinrich Jiang

Skill Discovery for Exploration and Planning using Deep Skill Graphs

Akhil Bagaria, Jason K Senthil, George Konidaris

Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees

Kishan Panaganti Badrinath, Dileep Kalathil

Faster Kernel Matrix Algebra via Density Estimation

Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner

Uniform Convergence, Adversarial Spheres and a Simple Remedy

Gregor Bachmann, Seyed-Mohsen Moosavi-Dezfooli, Thomas Hofmann

On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification

Zahra Babaiee, Ramin Hasani, Mathias Lechner, Daniela Rus, Radu Grosu

On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent

Shahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake E Woodworth, Nathan Srebro

Differentially Private Query Release Through Adaptive Projection

Sergul Aydore, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis

Decomposable Submodular Function Minimization via Maximum Flow

Kyriakos Axiotis, Adam Karczmarz, Anish Mukherjee, Piotr Sankowski, Adrian Vladu

Asynchronous Distributed Learning : Adapting to Gradient Delays without Prior Knowledge

Rotem Zamir Aviv, Ido Hakimi, Assaf Schuster, Kfir Yehuda Levy

Federated Learning under Arbitrary Communication Patterns

Dmitrii Avdiukhin, Shiva Kasiviswanathan

Dichotomous Optimistic Search to Quantify Human Perception

Julien Audiffren

Combinatorial Blocking Bandits with Stochastic Delays

Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu, Constantine Caramanis, Sanjay Shakkottai

Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry

Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar

Private Adaptive Gradient Methods for Convex Optimization

Hilal Asi, John Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar

Deciding What to Learn: A Rate-Distortion Approach

Dilip Arumugam, Benjamin Van Roy

Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients

Artem Artemev, David R. Burt, Mark van der Wilk

Dropout: Explicit Forms and Capacity Control

Raman Arora, Peter Bartlett, Poorya Mianjy, Nathan Srebro

Analyzing the tree-layer structure of Deep Forests

Ludovic Arnould, Claire Boyer, Erwan Scornet

Permutation Weighting

David Arbour, Drew Dimmery, Arjun Sondhi

Annealed Flow Transport Monte Carlo

Michael Arbel, Alex Matthews, Arnaud Doucet

The Logical Options Framework

Brandon Araki, Xiao Li, Kiran Vodrahalli, Jonathan DeCastro, Micah Fry

Unitary Branching Programs: Learnability and Lower Bounds

Fidel Ernesto Diaz Andino, Maria Kokkou, Mateus de Oliveira Oliveira, Farhad Vadiee

Preferential Temporal Difference Learning

Nishanth Anand, Doina Precup

Locally Persistent Exploration in Continuous Control Tasks with Sparse Rewards

Susan Amin, Maziar Gomrokchi, Hossein Aboutalebi, harsh satija, Doina Precup

Sparse Bayesian Learning via Stepwise Regression

Sebastian E. Ament, Carla P. Gomes

Automatic variational inference with cascading flows

Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven

Safe Reinforcement Learning with Linear Function Approximation

Sanae Amani, CHRISTOS THRAMPOULIDIS, Lin Yang

Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive Complexity

Georgios Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Alberto Marchetti-Spaccamela

Dataset Dynamics via Gradient Flows in Probability Space

David Alvarez-Melis, Nicolo Fusi

Non-Exponentially Weighted Aggregation: Regret Bounds for Unbounded Loss Functions

Pierre Alquier

Communication-Efficient Distributed Optimization with Quantized Preconditioners

Foivos Alimisis, Peter Davies, Dan Alistarh

Robust Pure Exploration in Linear Bandits with Limited Budget

Ayya Alieva, Ashok Cutkosky, Abhimanyu Das

A large-scale benchmark for few-shot program induction and synthesis

Ferran Alet, Javier Lopez-Contreras, James Koppel, Maxwell Nye, Armando Solar-Lezama

Slot Machines: Discovering Winning Combinations of Random Weights in Neural Networks

Maxwell M Aladago, Lorenzo Torresani

On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting

Shunta Akiyama, Taiji Suzuki

How Does Loss Function Affect Generalization Performance of Deep Learning? Application to Human Age Estimation

Ali Akbari, Muhammad Awais, Manijeh Bashar, Josef Kittler

Deep kernel processes

Laurence Aitchison, Adam Yang, Sebastian W. Ober

Label Inference Attacks from Log-loss Scores

Abhinav Aggarwal, Shiva Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier

Towards the Unification and Robustness of Perturbation and Gradient Based Explanations

Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu

A Regret Minimization Approach to Iterative Learning Control

Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh

Acceleration via Fractal Learning Rate Schedules

Naman Agarwal, Surbhi Goel, Cyril Zhang

Towards Rigorous Interpretations: a Formalisation of Feature Attribution

Darius Afchar, Vincent Guigue, Romain Hennequin

f-Domain Adversarial Learning: Theory and Algorithms

David Acuna, Guojun Zhang, Marc T. Law, Sanja Fidler

GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning

Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya

Robust Testing and Estimation under Manipulation Attacks

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

Memory Efficient Online Meta Learning

Durmus Alp Emre Acar, Ruizhao Zhu, Venkatesh Saligrama

Debiasing Model Updates for Improving Personalized Federated Training

Durmus Alp Emre Acar, Yue Zhao, Ruizhao Zhu, Ramon Matas, Matthew Mattina

Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling

Kuruge Darshana Abeyrathna, Bimal Bhattarai, Morten Goodwin, Saeed Rahimi Gorji, Ole-Christoffer Granmo

A New Representation of Successor Features for Transfer across Dissimilar Environments

Majid Abdolshah, Hung Le, Thommen Karimpanal George, Sunil Gupta, Santu Rana