ICML

Multi-Sender Persuasion: A Computational Perspective

Safwan Hossain, Tonghan Wang, Tao Lin, Yiling Chen, David C. Parkes, Haifeng Xu

Comments Accepted by ICML 2024

FRAPPE: A Group Fairness Framework for Post-Processing Everything

Alexandru Tifrea, Preethi Lahoti, Ben Packer, Yoni Halpern, Ahmad Beirami, Flavien Prost

Comments Conference paper at ICML 2024

Deciphering RNA Secondary Structure Prediction: A Probabilistic K-Rook Matching Perspective

Cheng Tan, Zhangyang Gao, Hanqun Cao, Xingran Chen, Ge Wang, Lirong Wu, Jun Xia, Jiangbin Zheng, Stan Z. Li

Comments Accepted by ICML 2024

EVEREST: Efficient Masked Video Autoencoder by Removing Redundant Spatiotemporal Tokens

Sunil Hwang, Jaehong Yoon, Youngwan Lee, Sung Ju Hwang

Comments Accepted by ICML 2024

A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction

Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

Comments This paper has been accepted to ICML 24 as a poster. You are encouraged to cite the conference version of this paper

MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation

Alexandre Hayderi, Amin Saberi, Ellen Vitercik, Anders Wikum

Comments Accepted to ICML 2024; Hardness result from introduction made precise

On the Diminishing Returns of Width for Continual Learning

Etash Guha, Vihan Lakshman

Comments 25 pages. ICML 2024

Evolving AI Collectives to Enhance Human Diversity and Enable Self-Regulation

Shiyang Lai, Yujin Potter, Junsol Kim, Richard Zhuang, Dawn Song, James Evans

Comments ICML 2024

LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views

Yuji Roh, Qingyun Liu, Huan Gui, Zhe Yuan, Yujin Tang, Steven Euijong Whang, Liang Liu, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao

Comments In Proceedings of the 41st International Conference on Machine Learning (ICML), 2024

Discounted Adaptive Online Learning: Towards Better Regularization

Zhiyu Zhang, David Bombara, Heng Yang

Comments ICML 2024

Differentially Private Bias-Term Fine-tuning of Foundation Models

Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

Comments Accepted at ICML 2024

In-Context Learning of Energy Functions

Rylan Schaeffer, Mikail Khona, Sanmi Koyejo

Comments Proceedings of the 1st Workshop on In-Context Learning at the 41st International Conference on Machine Learning, Vienna, Austria. 2024. arXiv admin note: text overlap with arXiv:2402.10202

A data-centric approach for assessing progress of Graph Neural Networks

Tianqi Zhao, Ngan Thi Dong, Alan Hanjalic, Megha Khosla

Journal ref Published in Data-centric Machine Learning Research Worshop @ ICML 2024

A Rate-Distortion View of Uncertainty Quantification

Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen, Artur Dubrawski

Journal ref International Conference on Machine Learning, 2024

Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency

Alan Nawzad Amin, Andrew Gordon Wilson

Comments ICML 2024; Code at https://github.com/AlanNawzadAmin/DAT-graph

Preventing Model Collapse in Gaussian Process Latent Variable Models

Ying Li, Zhidi Lin, Feng Yin, Michael Minyi Zhang

Comments International Conference on Machine Learning (ICML), 2024

How Graph Neural Networks Learn: Lessons from Training Dynamics

Chenxiao Yang, Qitian Wu, David Wipf, Ruoyu Sun, Junchi Yan

Comments Accepted to ICML 2024

Is persona enough for personality? Using ChatGPT to reconstruct an agent's latent personality from simple descriptions

Yongyi Ji, Zhisheng Tang, Mayank Kejriwal

Comments Accepted to the ICML 2024 Workshop on Large Language Models and Cognition

EvIL: Evolution Strategies for Generalisable Imitation Learning

Silvia Sapora, Gokul Swamy, Chris Lu, Yee Whye Teh, Jakob Nicolaus Foerster

Comments 17 pages, 8 figures, ICML 2024

Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss

Zhenlong Liu, Lei Feng, Huiping Zhuang, Xiaofeng Cao, Hongxin Wei

Comments Accepted by ICML 2024

Online Cascade Learning for Efficient Inference over Streams

Lunyiu Nie, Zhimin Ding, Erdong Hu, Christopher Jermaine, Swarat Chaudhuri

Comments ICML 2024 Main Conference Paper

Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Yongshuo Zong, Ondrej Bohdal, Tingyang Yu, Yongxin Yang, Timothy Hospedales

Comments ICML 2024

Learning Rate Schedules in the Presence of Distribution Shift

Matthew Fahrbach, Adel Javanmard, Vahab Mirrokni, Pratik Worah

Comments 33 pages, 6 figures

Journal ref Proceedings of the 40th International Conference on Machine Learning (ICML 2023) 9523-9546

Approximately Optimal Core Shapes for Tensor Decompositions

Mehrdad Ghadiri, Matthew Fahrbach, Gang Fu, Vahab Mirrokni

Comments 18 pages, 4 figures

Journal ref Proceedings of the 40th International Conference on Machine Learning (ICML 2023) 11237-11254

Faster Graph Embeddings via Coarsening

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

Comments 18 pages, 2 figures, to appear in the Proceedings of the 37th International Conference on Machine Learning (ICML 2020)

Journal ref Proceedings of the 37th International Conference on Machine Learning (ICML 2020) 2953-2963

Making Old Things New: A Unified Algorithm for Differentially Private Clustering

Max Dupré la Tour, Monika Henzinger, David Saulpic

Comments Oral presentation at ICML 2024

ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking

Wenshuo Li, Xinghao Chen, Han Shu, Yehui Tang, Yunhe Wang

Comments ICML 2024 oral

Learning Iterative Reasoning through Energy Diffusion

Yilun Du, Jiayuan Mao, Joshua B. Tenenbaum

Comments ICML 2024, website: https://energy-based-model.github.io/ired/

Fine-grained Classes and How to Find Them

Matej Grcić, Artyom Gadetsky, Maria Brbić

Comments Accepted to ICML 2024

First-Order Manifold Data Augmentation for Regression Learning

Ilya Kaufman, Omri Azencot

Comments Accepted to ICML 2024