ICML

Thinking Like Transformers

Gail Weiss, Yoav Goldberg, Eran Yahav

Comments ICML 2021

Exploration and preference satisfaction trade-off in reward-free learning

Noor Sajid, Panagiotis Tigas, Alexey Zakharov, Zafeirios Fountas, Karl Friston

Comments 23 pages, 15 figures

Journal ref Proceedings of the Unsupervised Reinforcement Learning Workshop ICML 2021

Efficient Optimal Transport Algorithm by Accelerated Gradient descent

Dongsheng An, Na Lei, Xianfeng Gu

Comments ICML 2021 workshop for Beyond first-order methods in machine learning systems

Towards the Unification and Robustness of Perturbation and Gradient Based Explanations

Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Zhiwei Steven Wu, Himabindu Lakkaraju

Comments The short version of this paper appears in the proceedings of ICML-21

STRODE: Stochastic Boundary Ordinary Differential Equation

Hengguan Huang, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang

Comments Accepted at ICML 2021; typos corrected

Learning De-identified Representations of Prosody from Raw Audio

Jack Weston, Raphael Lenain, Udeepa Meepegama, Emil Fristed

Comments ICML 2021

Journal ref Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event. Proceedings of Machine Learning Research 139, PMLR 2021

Robust Risk-Sensitive Reinforcement Learning Agents for Trading Markets

Yue Gao, Kry Yik Chau Lui, Pablo Hernandez-Leal

Comments Reinforcement Learning for Real Life (RL4RealLife) Workshop at ICML 2021

Refined Policy Improvement Bounds for MDPs

J. G. Dai, Mark Gluzman

Comments Workshop on Reinforcement Learning Theory, ICML 2021

Understanding Failures in Out-of-Distribution Detection with Deep Generative Models

Lily H. Zhang, Mark Goldstein, Rajesh Ranganath

Comments Accepted at ICML 2021

Deep Contextual Learners for Protein Networks

Michelle M. Li, Marinka Zitnik

Comments Accepted to the 2021 International Conference on Machine Learning (ICML) Workshop on Computational Biology (WCB)

Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning

Hassan Hafez-Kolahi, Behrad Moniri, Shohreh Kasaei, Mahdieh Soleymani Baghshah

Comments Accepted at ICML 2021

Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality

Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang

Comments Published in ICML 2021

Making transport more robust and interpretable by moving data through a small number of anchor points

Chi-Heng Lin, Mehdi Azabou, Eva L. Dyer

Journal ref International Conference on Machine Learning (ICML) 2021

Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes

Peter Holderrieth, Michael Hutchinson, Yee Whye Teh

Journal ref Proceedings of the 38th International Conference on Machine Learning, PMLR 139, 2021

Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games

Tianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael I. Jordan

Comments Accepted by ICML 2020; The first two authors contributed equally to this work

Single Pass Entrywise-Transformed Low Rank Approximation

Yifei Jiang, Yi Li, Yiming Sun, Jiaxin Wang, David P. Woodruff

Comments Accepted to ICML 2021

A Causal Perspective on Meaningful and Robust Algorithmic Recourse

Gunnar König, Timo Freiesleben, Moritz Grosse-Wentrup

Comments ICML (International Conference on Machine Learning) Workshop on Algorithmic Recourse

Contrastive Predictive Coding for Anomaly Detection

Puck de Haan, Sindy Löwe

Comments 7 pages, ICML 2021 Workshop on Uncertainty and Robustness in Deep Learning

Measuring Fairness in Generative Models

Christopher T. H Teo, Ngai-Man Cheung

Comments Accepted in ICML 2021 Workshop - Machine Learning for Data: Automated Creation, Privacy, Bias

Beyond In-Place Corruption: Insertion and Deletion In Denoising Probabilistic Models

Daniel D. Johnson, Jacob Austin, Rianne van den Berg, Daniel Tarlow

Comments Accepted at the ICML 2021 Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models (poster)

Streaming and Distributed Algorithms for Robust Column Subset Selection

Shuli Jiang, Dongyu Li, Irene Mengze Li, Arvind V. Mahankali, David P. Woodruff

Comments Proceedings of the 38th International Conference on Machine Learning (ICML 2021)

Evaluating subgroup disparity using epistemic uncertainty in mammography

Charles Lu, Andreanne Lemay, Katharina Hoebel, Jayashree Kalpathy-Cramer

Comments Accepted to the Interpretable Machine Learning in Healthcare workshop at the ICML 2021 conference

From Local Structures to Size Generalization in Graph Neural Networks

Gilad Yehudai, Ethan Fetaya, Eli Meirom, Gal Chechik, Haggai Maron

Comments Camera ready version for ICML 2021

On Disentangled Representations Learned From Correlated Data

Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer

Comments Published at the 38th International Conference on Machine Learning (ICML 2021)

Personalized and Reliable Decision Sets: Enhancing Interpretability in Clinical Decision Support Systems

Francisco Valente, Simão Paredes, Jorge Henriques

Comments Accepted to the ICML 2021 Workshop on Interpretable Machine Learning in Healthcare

Copula-Based Normalizing Flows

Mike Laszkiewicz, Johannes Lederer, Asja Fischer

Comments Accepted for presentation at the ICML 2021 Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models (INNF+ 2021)

Mutation is all you need

Lennart Schneider, Florian Pfisterer, Martin Binder, Bernd Bischl

Comments Accepted for the 8th ICML Workshop on Automated Machine Learning (2021). 10 pages, 1 table, 3 figures

Mitigating Memorization in Sample Selection for Learning with Noisy Labels

Kyeongbo Kong, Junggi Lee, Youngchul Kwak, Young-Rae Cho, Seong-Eun Kim, Woo-Jin Song

Comments 14 pages, 9 figures, spotlight presented at the ICML 2021 Workshop on Subset Selection in ML

Short-term Hourly Streamflow Prediction with Graph Convolutional GRU Networks

Muhammed Sit, Bekir Demiray, Ibrahim Demir

Comments 4 pages, Accepted to Tackling Climate Change with Machine Learning workshop at ICML 2021

Elastic Graph Neural Networks

Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang

Comments ICML 2021 (International Conference on Machine Learning)