The BayLearn Symposium aims at gathering scientists in machine learning from the San Francisco Bay Area. While it promotes community building between local researchers from academic and industrial institutions, it also welcomes visitors. This one-day event combines invited talks and posters to foster exchange of ideas.
We encourage the submission of poster abstracts. Acceptable material includes work which has already been submitted or published, preliminary results and controversial findings... All accepted abstracts will be presented as posters, a few will be selected for short oral presentations or lightning talks. We do not intend to publish proceedings, only abstracts will be shared through an online repository. Our primary goal is to foster discussion!
- BayLearn 2023 will be hosted in-person hosted by Block Inc. (formerly Square Inc.). Registered attendees: please follow the instruction in the email (titled "BayLearn 2023: See you Thursday!") to get to the venue.
No onsite registration! Don't forget to bring a govt. issued photo ID.
Important Dates for BayLearn 2023
- Abstract submission deadline (EXTENDED): Thursday, July 13, 2023 11:59pm PDT
- Acceptance notification: Wednesday, Sep 20th, 2023
- Registration for attending opens: Monday, Sep 25th 2023
- Registration for attending closes: Tuesday, Oct 10th 2023
- Registration for lottery results via email: Thursday, Oct 12th 2023
- BayLearn Symposium: Thursday, October 19th, 2023
Registration is currently CLOSED.
Please join the BayLearn Mailing List for receiving symposium related announcements.
info at baylearn dot org
- Jerremy Holland, Apple
- Jean-François Paiement, AT&T Research
- Sudarshan Lamkhede, Netflix Research
- Isabelle Guyon, Google, ChaLearn, and U. Paris-Saclay
- Dumitru Erhan, Google