The BayLearn 2023 abstract submission site is now open for submissions:
https://baylearn.org/submissions
The abstract submission deadline is Friday, June 30th, 2023, 11:59pm PDT.
Please submit abstracts as a 2-page pdf in NeurIPS format. An extra page for acknowledgements and references is allowed.
About BayLearn
BayLearn 2023 will be an in-person event, hosted in Oakland, CA, on Thursday, October 19th, 2023.
Note: BayLearn 2023 will not be a hybrid event, and it will not be live-streamed.
The BayLearn Symposium is an annual gathering of machine learning researchers and scientists from the San Francisco Bay Area. While BayLearn promotes community building and technical discussions between local researchers from academic and industrial institutions, it also welcomes visitors. This one-day event combines invited talks, contributed talks, and posters, to foster exchange of ideas.
Meet with fellow Bay Area machine learning researchers and scientists during the symposium that will be held on October 19th, in Oakland, California.
Feel free to circulate this invitation to your colleagues and relevant contacts.
Key Dates
Friday, June 30th, 2023 at 11:59pm PDT - Abstract submission deadline
Thursday, September 14th, 2023 - Acceptance notifications—IMPORTANT: If your abstract is selected, at least one author must attend the event in person.
Thursday, October 19th, 2023 - BayLearn 2023 Symposium. We are planning for BayLearn 2023 to be an in-person event, to be held on Thursday, October 19, 2023, in Oakland, with venue details to be announced prior to the submission deadline.
Submissions
We encourage submission of abstracts. Acceptable material includes work which has already been submitted or published, preliminary results, and controversial findings. We do not intend to publish paper proceedings; only abstracts will be shared through an online repository. Our primary goal is to foster discussion! For examples of previously accepted talks, please watch the paper presentations from previous BayLearn Symposiums: https://baylearn.org/previous
For more information about submissions, please look here:
https://baylearn.org/submissions
Submit your abstracts via CMT:
https://cmt3.research.microsoft.com/BAYLEARN2023
Mailing List: If this email was forwarded to you, and you would like to join the BayLearn mailing list so that you will receive future communications from us directly, please sign up here.
Best Regards,
The BayLearn Organizers