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Journal of Machine Learning Research (JMLR)

Proceedings of Machine Learning Research (PMLR)

Data-centric Machine Learning Research (DMLR)

TMLR guidelines for authors

This document provides instructions for authors. Authors are required to also read and be familiar with the Editorial Policies, the Acceptance Criteria, the Ethics Guidelines, and the Code of Conduct

Overview of submission process

TMLR uses a double blind review process and submissions must be anonymized. All authors must create author profiles and give conflict of interest information. They also must provide information on appropriate action editors for the submission, as well as on human subjects reporting (IRB), funding, competing interests and any conflict of interest not covered by the institutional history of the authors. Such information will not be disclosed to the reviewers, but will be once a decision on the manuscript has been made.

Following submission, an action editor will be assigned and the paper will be evaluated to check that it meets the criteria for the review process; e.g. it should be in scope, anonymous, and complete. Then reviewers will be assigned to read and review the manuscript. An open-ended rebuttal, discussion, and revision phase will allow authors to interact with reviewers and update their paper. Finally, the action editor will enter a decision, either accept as is, accept with minor revisions, or reject. See the Submission Guidelines and Editorial Policies, as well as the Reviewer and Action Editor Guidelines, for more information.

Broader impact statement

If their work carries a significant risk of harm, authors are required to include a Statement of Broader Impact. The statement should include a concise, concrete description of potential positive and negative societal impact, as well as a discussion of possible mitigations. Please read the discussion in the Ethics Guidelines for an in depth discussion of possible risks and mitigating factors.  

Format

Submissions may be any length, but a paper’s length should be justified by its content and papers that are unusually long (not counting any Appendices) are likely to result in reviewing delays. Submissions must be PDF files generated using the TMLR LaTeX stylefile and template. The submission PDF may include an Appendix, after the references (for proofs, derivations or complimentary results). Looking at the Appendix is at the discretion of the reviewers.

Authors may submit up to 100MB of supplementary material, such data, source code or illustrative videos; all supplementary materials must be in PDF or ZIP format. Supplementary material should be material created by the authors that directly supports the submission content. Like submissions, supplementary material must be anonymized. Looking at supplementary material is at the discretion of the reviewers.

We encourage authors to, whenever possible, upload materials that improve reproducibility. Specifically, it is suggested that authors submit supplementary material including data or code towards this end.

Copyright and Licensing

All TMLR submissions, from the time of submission to final publication, are licensed under CC BY 4.0. At all times, copyright is retained by the authors. Authors are also allowed to upload their submissions to arXiv or other preprint servers at any time, either anonymously or including their identity, though double blind of the TMLR submission itself must be maintained by not linking to another version that includes the authors' names.

© TMLR 2024.
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