The 41st International Conference on Machine Learning (ICML 2024) will be held in Vienna, Austria, July 21st - 27th, and is planned to be an in person conference with virtual elements. In addition to the main conference sessions, the conference will also include Expo, Tutorials, and Workshops. Please submit proposals to the appropriate chairs.

We invite submissions of papers on all topics related to machine learning for the main conference proceedings. All papers will be reviewed in a double-blind process and accepted papers will be presented at the conference. As with last year, papers need to be prepared and submitted as a single file: 8 pages as main paper, with unlimited pages for references and appendix. There will be no separate deadline for the submission of supplementary material. In addition, we require that, barring exceptional circumstances (such as visa problems) upon the acceptance of their papers, at least one of the authors must attend the conference, in person.

Topics of interest include (but are not limited to):

    General Machine Learning (active learning, clustering, online learning, ranking, reinforcement learning, supervised, semi- and self-supervised learning, time series analysis, etc.)
    Deep Learning (architectures, generative models, deep reinforcement learning, etc.)
    Learning Theory (bandits, game theory, statistical learning theory, etc.)
    Optimization (convex and non-convex optimization, matrix/tensor methods, stochastic, online, non-smooth, composite, etc.)
    Probabilistic Inference (Bayesian methods, graphical models, Monte Carlo methods, etc.)
    Trustworthy Machine Learning (accountability, causality, fairness, privacy, robustness, etc.)
    Applications (computational biology, crowdsourcing, healthcare, neuroscience, social good, climate science, etc.) - we do welcome strong application papers even if there is no new method or theory

This year we are introducing a separate track for position papers. Please consider submitting to this track if you feel that your work would be a better fit for this track instead of the main conference track. We anticipate similar acceptance rates for this track and the main conference track.

Papers published at ICML are indexed in the Proceedings of Machine Learning Research through the Journal of Machine Learning Research.