Call For Papers

       The 40th International Conference on Machine Learning (ICML 2022) will be held in Honolulu, Hawaii USA July 23rd - July 29th, 2023, 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.

 

Important Dates:

       As noted above, this year, ICML will use a single paper submission deadline with a single review cycle, as follows.

       Submissions open Jan 9th, 2023.

       Full paper submission deadline Jan 26th, 2023 3pm EST.

       Abstracts and papers can be submitted through OpenReview: https://openreview.net/group?id=ICML.cc/2023/Conference

 

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.

 

Policies

Deadlines:

       Abstract and paper submission deadlines are strict. In no circumstances will extensions be given.

 

Changes of title/abstract/authorship:

       Authors should include a full title for their paper, as well as a complete paper by the paper submission deadline. Submission titles should not be modified after the paper submission deadline. Submissions violating these rules may be deleted after the paper submission deadline without reviewing. The author list at the paper submission deadline will be considered final, and no changes in authorship will be permitted for accepted papers.

 

Double-Blind Review:

       All submissions must be anonymized and may not contain any information with the intention or consequence of violating the double-blind reviewing policy, including (but not limited to) citing previous works of the authors or sharing links in a way that can infer any author’s identity or institution, actions that reveal the identities of the authors to potential reviewers.

       Authors are allowed to post versions of their work on preprint servers such as arXiv. They are also allowed to give talks to restricted audiences on the work(s) submitted to ICML during the review. If you have posted or plan to post a non-anonymized version of your paper online before the ICML decisions are made, the submitted version must not refer to the non-anonymized version.

       ICML strongly discourages advertising the preprint on social media or in the press while under submission to ICML. Under no circumstances should your work be explicitly identified as ICML submission at any time during the review period, i.e., from the time you submit the paper to the communication of the accept/reject decisions.

 

Dual Submission:

       It is not appropriate to submit papers that are identical (or substantially similar) to versions that have been previously published, accepted for publication, or submitted in parallel to other conferences or journals. Such submissions violate our dual submission policy, and the organizers have the right to reject such submissions, or to remove them from the proceedings. Note that submissions that have been or are being presented at workshops do not violate the dual-submission policy, as long as there’s no associated archival publication.

 

Reviewing Criteria:

       Accepted papers must be based on original research and must contain novel results of significant interest to the machine learning community. Results can be either theoretical or empirical. Results will be judged on the degree to which they have been objectively established and/or their potential for scientific and technological impact. Reproducibility of results and easy availability of code will be taken into account in the decision-making process whenever appropriate.

 

Ethics:

       Authors and members of the program committee, including reviewers, are expected to follow standard ethical guidelines. Plagiarism in any form is strictly forbidden as is unethical use of privileged information by reviewers, ACs, and SACs, such as sharing this information or using it for any other purpose than the reviewing process. Papers that include text generated from a large-scale language model (LLM) such as ChatGPT are prohibited unless these produced text is presented as a part of the paper’s experimental analysis. All suspected unethical behaviors will be investigated by an ethics board and individuals found violating the rules may face sanctions. This year, we will collect names of individuals that have been found to have violated these standards; if individuals representing conferences, journals, or other organizations request this list for decision making purposes, we may make this information available to them.

Details of the LLM guideline are now available here.

 

Financial aid:

       Each paper submission may, by providing a corresponding icml.cc account email address, designate up to one student author who, should the paper be accepted, would not be able to present the work unless partially supported by a grant from the conference.  Doing so confirms (1) financial need, (2) intention to attend and present in person and (3) willingness to volunteer at the conference for two 4 hour shifts.  ICML aims to provide free conference registration and hotel registration for at least part of the week.  The number of such awards are limited.

 

OpenReview and Rankings:

       This year we will use OpenReview and we will require that authors of multiple submissions, upon submission confirmation, submit a rank ordering of their papers from their own perspective. For this year, we seek this information to assess consistency of self-perception with respect to review outcomes. We will not share rankings with co-authors, reviewers, ACs, or SACs. Rankings will not be used in decision-making processes.

 

       Author Instructions, Style Files and an Example Paper. Submitted papers that do not conform to these policies will be rejected without review. Authors are kindly asked to make their submissions as accessible as possible for everyone including people with disabilities and sensory or neurological differences.

 

       More information about ICML 2023 is available at: https://icml.cc/Conferences/2023​