Conference Information
ICML 2022: International Conference on Machine Learning
https://icml.cc/Conferences/2022
Submission Date:
2022-01-20
Notification Date:
Conference Date:
2022-07-17
Location:
Online
Years:
39
CCF: a   CORE: a*   QUALIS: a1   Viewed: 146509   Tracked: 556   Attend: 29

Call For Papers
The 39th International Conference on Machine Learning (ICML 2022) will be held in Baltimore, Maryland USA July 17-23, 2022 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. There are three important changes in the reviewing, paper formatting and submission process compared to last year: (i) Reviewing will take place in two phases. (ii) Papers need to be prepared and submitted as a single file: 8 pages as main paper, with unlimited pages for references and appendix. (iii) There will be no separate deadline for the submission of supplementary material. In addition, a new requirement is that upon the acceptance of their papers, at least one of the authors must join the conference, either in person or virtually, or their paper will not be included in the proceedings.

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.)

Papers published at ICML are indexed in the Proceedings of Machine Learning Research through the Journal of Machine Learning Research.
Last updated by Dou Sun in 2021-12-04
Acceptance Ratio
YearSubmittedAcceptedAccepted(%)
20204990108821.8%
2019342477322.6%
2018247362125.1%
2017167643425.9%
2015103727026%
201289024227.2%
201158915225.8%
201059415225.6%
200959516026.9%
200858315526.6%
200752215028.7%
200670014020%
200549113427.3%
200436811832.1%
200337111932.1%
20022618633%
20012498032.1%
200034915143.3%
19991525435.5%
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Related Journals
CCFFull NameImpact FactorPublisherISSN
aJournal of Machine Learning Research Microtome Publishing1532-4435
International Journal of Modern Physics CWorld Scientific0129-1831
cMachine TranslationSpringer0922-6567
Foundations and Trends in Machine LearningNow Publishers Inc.1935-8237
Electronic Journal of e-LearningAcademic Publishing Limited1479-4403
Journal of Function Spaces0.451Hindawi2314-8896
Engineering7.553Elsevier2095-8099
Wireless Power TransferCambridge University Press2052-8418
MachinesMDPI2075-1702
IEEE Transactions on Technology and SocietyIEEE2637-6415
Full NameImpact FactorPublisher
Journal of Machine Learning Research Microtome Publishing
International Journal of Modern Physics CWorld Scientific
Machine TranslationSpringer
Foundations and Trends in Machine LearningNow Publishers Inc.
Electronic Journal of e-LearningAcademic Publishing Limited
Journal of Function Spaces0.451Hindawi
Engineering7.553Elsevier
Wireless Power TransferCambridge University Press
MachinesMDPI
IEEE Transactions on Technology and SocietyIEEE
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