ICML

On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology

Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio', Michael Bronstein

Comments Accepted at ICML 2023; 21 pages

Measuring The Impact Of Programming Language Distribution

Gabriel Orlanski, Kefan Xiao, Xavier Garcia, Jeffrey Hui, Joshua Howland, Jonathan Malmaud, Jacob Austin, Rishabh Singh, Michele Catasta

Comments Accepted to ICML 2023, Code and data release: https://github.com/google-research/babelcode

Learning Antidote Data to Individual Unfairness

Peizhao Li, Ethan Xia, Hongfu Liu

Comments Accepted by ICML'23

Biological Sequence Design with GFlowNets

Moksh Jain, Emmanuel Bengio, Alex-Hernandez Garcia, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ekbote, Jie Fu, Tianyu Zhang, Micheal Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio

Comments ICML 2022. 15 pages, 3 figures. Code available at: https://github.com/MJ10/BioSeq-GFN-AL. Updated GFP results

Provably Learning Object-Centric Representations

Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius von Kügelgen, Wieland Brendel

Comments Oral at ICML 2023. The first two authors as well as the last two authors contributed equally. Code is available at https://brendel-group.github.io/objects-identifiability

Learning Subpocket Prototypes for Generalizable Structure-based Drug Design

Zaixi Zhang, Qi Liu

Comments Accepted by ICML 2023

Covariate balancing using the integral probability metric for causal inference

Insung Kong, Yuha Park, Joonhyuk Jung, Kwonsang Lee, Yongdai Kim

Comments 32 pages, ICML 2023 proceedings

Dual Focal Loss for Calibration

Linwei Tao, Minjing Dong, Chang Xu

Comments ICML 2023 Accept

Tied-Augment: Controlling Representation Similarity Improves Data Augmentation

Emirhan Kurtulus, Zichao Li, Yann Dauphin, Ekin Dogus Cubuk

Comments 14 pages, 2 figures, ICML 2023

SE(3) diffusion model with application to protein backbone generation

Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi Jaakkola

Journal ref International Conference of Machine Learning (ICML) 2023

Sampling-based Nyström Approximation and Kernel Quadrature

Satoshi Hayakawa, Harald Oberhauser, Terry Lyons

Comments 22 pages, ICML 2023 camera-ready version. Typos fixed

Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti's Theorem for Markov Chains

Buddhika Nettasinghe, Samrat Chatterjee, Ramakrishna Tipireddy, Mahantesh Halappanavar

Comments Accepted to the International Conference on Machine Learning (ICML), 2023

Target-Aware Generative Augmentations for Single-Shot Adaptation

Kowshik Thopalli, Rakshith Subramanyam, Pavan Turaga, Jayaraman J. Thiagarajan

Comments Accepted at International Conference Machine Learning (ICML) 2023

Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice

Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Rémi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvári, Wataru Kumagai, Yutaka Matsuo

Comments ICML 2023 accepted

PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation

Eli Chien, Jiong Zhang, Cho-Jui Hsieh, Jyun-Yu Jiang, Wei-Cheng Chang, Olgica Milenkovic, Hsiang-Fu Yu

Comments ICML 2023

Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining

Zekun Qi, Runpei Dong, Guofan Fan, Zheng Ge, Xiangyu Zhang, Kaisheng Ma, Li Yi

Comments Accepted at ICML 2023

Personalized Subgraph Federated Learning

Jinheon Baek, Wonyong Jeong, Jiongdao Jin, Jaehong Yoon, Sung Ju Hwang

Comments ICML 2023

Streaming Inference for Infinite Non-Stationary Clustering

Rylan Schaeffer, Gabrielle Kaili-May Liu, Yilun Du, Scott Linderman, Ila Rani Fiete

Comments Published at the Workshop on Agent Learning in Open-Endedness (ALOE) at ICLR 2022

Journal ref Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19366-19387, 2022

Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework

Arman Rahbar, Ashkan Panahi, Morteza Haghir Chehreghani, Devdatt Dubhashi, Hamid Krim

Comments Accepted in 40th International Conference on Machine Learning (ICML 2023)

Bandit Multi-linear DR-Submodular Maximization and Its Applications on Adversarial Submodular Bandits

Zongqi Wan, Jialin Zhang, Wei Chen, Xiaoming Sun, Zhijie Zhang

Comments Accepted by ICML 2023

Lifelong Language Pretraining with Distribution-Specialized Experts

Wuyang Chen, Yanqi Zhou, Nan Du, Yanping Huang, James Laudon, Zhifeng Chen, Claire Cu

Comments ICML 2023

Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments

Runlong Zhou, Zihan Zhang, Simon S. Du

Comments ICML 2023

BiBench: Benchmarking and Analyzing Network Binarization

Haotong Qin, Mingyuan Zhang, Yifu Ding, Aoyu Li, Zhongang Cai, Ziwei Liu, Fisher Yu, Xianglong Liu

Journal ref 2023 International Conference on Machine Learning

Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes

Runlong Zhou, Ruosong Wang, Simon S. Du

Comments ICML 2023

EF21-P and Friends: Improved Theoretical Communication Complexity for Distributed Optimization with Bidirectional Compression

Kaja Gruntkowska, Alexander Tyurin, Peter Richtárik

Journal ref Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023

Differentiable Agent-based Epidemiology

Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Arnau Quera-Bofarull, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar

Comments Appears in AAMAS 2023 and ICML AI4ABM 2022 (best paper award)

Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models

Wenhao Ding, Tong Che, Ding Zhao, Marco Pavone

Comments Accepted to ICML 2023

Fast Inference from Transformers via Speculative Decoding

Yaniv Leviathan, Matan Kalman, Yossi Matias

Comments ICML 2023 Oral

Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion

Marin Biloš, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann

Comments International Conference on Machine Learning (ICML), 2023

Statistical Foundations of Prior-Data Fitted Networks

Thomas Nagler

Journal ref Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023