Abstract submission will close on Oct 3, 2023
Final paper submission will close on Oct 10 2023
Camera-ready final submission deadline: 24 Oct, 2023
Authors should include a full title for their paper, as well as a complete abstract in the fields provided. Author name(s) and organization/institution should be provided clearly. Submissions that have “placeholder” (test, xyz, etc.) titles or abstracts (or none at all) will not be accepted.
All the selected Abstracts would be contacted by MLDS team and they are required to send across the final paper.
Final Papers must be in trouble-free, high-resolution PDF format, formatted for US Letter (8.5″ x 11″) paper, using Type 1 or TrueType fonts. Submissions may have up to 8 pages with page 8 containing nothing but references. The last page of final papers may contain text other than references, but all references in the submitted paper should appear in the final version unless superseded.
The selected papers will be published in Lattice, The Machine Learning Journal by Association of Data Scientists.
MLDS will not consider any paper that, at the time of submission, is under review for or has already been published or accepted for publication in a journal or another conference.
Once submitted to MLDS, authors may not submit the paper elsewhere during MLDS’s review period. These restrictions apply only to refereed journals and conferences, not to unrefereed forums (e.g. arXiv.org) or workshops with a limited audience and without archival proceedings.
Authors must confirm that their submissions conform to these requirements at the time of submission.
At least one author is required to be available to present the paper.
Conference Presentation During paper presentation, authors will have to use Powerpoint. You will receive 20-minute oral presentation at MLDS. The timing/ slot for the same will be communicated to you beforehand.
All submitted papers would be printed as a compendium and shared with MLDS attendees.
Please make your submission below:
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Note: Ticket Pricing to change at any time.