ICML

Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data

Kang Lin, Reinhard Heckel

Comments ICML 2024

Algorithmic Collective Action in Machine Learning

Moritz Hardt, Eric Mazumdar, Celestine Mendler-Dünner, Tijana Zrnic

Comments Published at ICML 2023; Revision corrects epsilon-dependence in the analysis

FedBAT: Communication-Efficient Federated Learning via Learnable Binarization

Shiwei Li, Wenchao Xu, Haozhao Wang, Xing Tang, Yining Qi, Shijie Xu, Weihong Luo, Yuhua Li, Xiuqiang He, Ruixuan Li

Comments Accepted by ICML 2024

Position: Topological Deep Learning is the New Frontier for Relational Learning

Theodore Papamarkou, Tolga Birdal, Michael Bronstein, Gunnar Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Liò, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Veličković, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi

Comments Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria. PMLR 235, 2024

Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI

Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang

Comments Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria. PMLR 235, 2024

Stability-Informed Initialization of Neural Ordinary Differential Equations

Theodor Westny, Arman Mohammadi, Daniel Jung, Erik Frisk

Comments In Proceedings of the 41 st International Conference on Machine Learning

Imitation Learning from Purified Demonstrations

Yunke Wang, Minjing Dong, Yukun Zhao, Bo Du, Chang Xu

Comments ICML 2024

RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning

Yukinari Hisaki, Isao Ono

Comments Accepted at ICML 2024; Code: https://github.com/yhisaki/average-reward-drl

Can LLMs predict the convergence of Stochastic Gradient Descent?

Oussama Zekri, Abdelhakim Benechehab, Ievgen Redko

Comments 9 pages. Accepted to 1st ICML Workshop on In-Context Learning at ICML 2024

Non-clairvoyant Scheduling with Partial Predictions

Ziyad Benomar, Vianney Perchet

Comments Accepted as a conference paper at ICML 2024

eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Data

Bo Peng, Xinyi Ling, Ziru Chen, Huan Sun, Xia Ning

Comments ICML 2024; Bo Peng and Xinyi Ling contributed equally to this paper

Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations

Henrik Schopmans, Pascal Friederich

Journal ref Proceedings of the 41st International Conference on Machine Learning (ICML 2024), PMLR 235:43804-43827, 2024

Parallel Affine Transformation Tuning of Markov Chain Monte Carlo

Philip Schär, Michael Habeck, Daniel Rudolf

Comments 37 pages, 9 figures, 10 tables

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:43571-43607, 2024

Emergent Representations of Program Semantics in Language Models Trained on Programs

Charles Jin, Martin Rinard

Comments ICML 2024

Journal ref PMLR 235:22160-22184, 2024

Amortized Probabilistic Detection of Communities in Graphs

Yueqi Wang, Yoonho Lee, Pallab Basu, Juho Lee, Yee Whye Teh, Liam Paninski, Ari Pakman

Comments Accepted by the Structured Probabilistic Inference & Generative Modeling workshop of ICML 2024, Vienna, Austria

Inpainting Galaxy Counts onto N-Body Simulations over Multiple Cosmologies and Astrophysics

Antoine Bourdin, Ronan Legin, Matthew Ho, Alexandre Adam, Yashar Hezaveh, Laurence Perreault-Levasseur

Comments 7+4 pages, 3+1 figures, accepted at the ICML 2024 Workshop AI4Science

ReLUs Are Sufficient for Learning Implicit Neural Representations

Joseph Shenouda, Yamin Zhou, Robert D. Nowak

Comments Accepted to ICML 2024

Fool Your (Vision and) Language Model With Embarrassingly Simple Permutations

Yongshuo Zong, Tingyang Yu, Ruchika Chavhan, Bingchen Zhao, Timothy Hospedales

Comments ICML 2024; v3 fix typo

Penzai + Treescope: A Toolkit for Interpreting, Visualizing, and Editing Models As Data

Daniel D. Johnson

Comments Presented at the ICML 2024 Mechanistic Interpretability workshop (Spotlight). 5 pages

Synthetic Time Series for Anomaly Detection in Cloud Microservices

Mohamed Allam, Noureddine Boujnah, Noel E. O'Connor, Mingming Liu

Comments The paper has been accepted by the 10th International Conference on Machine Learning, Optimization and Data Science

A Likelihood-Based Generative Approach for Spatially Consistent Precipitation Downscaling

Jose González-Abad

Comments Accepted at ICML 2024 Machine Learning for Earth System Modeling workshop

Debiased Distribution Compression

Lingxiao Li, Raaz Dwivedi, Lester Mackey

Comments Published at ICML 2024

Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience

Martina G. Vilas, Federico Adolfi, David Poeppel, Gemma Roig

Comments Accepted at ICML 2024

Promises and Pitfalls of Generative Masked Language Modeling: Theoretical Framework and Practical Guidelines

Yuchen Li, Alexandre Kirchmeyer, Aashay Mehta, Yilong Qin, Boris Dadachev, Kishore Papineni, Sanjiv Kumar, Andrej Risteski

Comments ICML 2024

Unveiling the Potential of AI for Nanomaterial Morphology Prediction

Ivan Dubrovsky, Andrei Dmitrenko, Aleksei Dmitrenko, Nikita Serov, Vladimir Vinogradov

Journal ref Proceedings of the 41 st International Conference on Machine Learning. PMLR 235, 2024, 11957--11978

Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need

Shangda Yang, Vitaly Zankin, Maximilian Balandat, Stefan Scherer, Kevin Carlberg, Neil Walton, Kody J. H. Law

Comments Preprint ICML 2024

Efficient Pareto Manifold Learning with Low-Rank Structure

Weiyu Chen, James T. Kwok

Comments ICML 2024 (Spotlight)

Evaluating Fairness in Black-box Algorithmic Markets: A Case Study of Ride Sharing in Chicago

Yuhan Liu, Yuhan Zheng, Siyuan Zhang, Lydia T. Liu

Comments Accepted to the Humans, Algorithmic Decision-Making and Society: Modeling Interactions and Impact, co-located with the International Conference on Machine Learning, Vienna, Austria

Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process

Tian Ye, Zicheng Xu, Yuanzhi Li, Zeyuan Allen-Zhu

Comments video appeared in ICML 2024 tutorial

Classification of freshwater snails of the genus Radomaniola with multimodal triplet networks

Dennis Vetter, Muhammad Ahsan, Diana Delicado, Thomas A. Neubauer, Thomas Wilke, Gemma Roig

Comments Spotlight at ICML 2024 AI for Science workshop