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2016 Mobile Ad Summit
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BayLearn 2021
Thursday
, 
October 
11
 at 
8:00am
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Note: Registration closes on Tuesday, October 26th at 5:00PM PDT.  You must register to attend BayLearn 2021

 

 

 

 

Picture Credit: © Della Huff

Bay Area Machine Learning Symposium

The Bay Area Machine Learning Symposium is an annual gathering of machine learning scientists from the San Francisco Bay Area. While it 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 and posters to foster the exchange of ideas.

Keynote Speakers

Anima Anandkumar

Caltech, NVidia

Keynote Talk:

AI4Science: Enabling Zero-Shot Generalization


More Info

Eric Horvitz

Microsoft, Partnership on AI

Keynote Talk:
People, Machines, and Intelligence: Pathways to Deeper Human-AI Synergy

 

More Info

Jure Leskovec

Stanford University

Keynote Talk: 
Scaling-up Knowledge Graph Reasoning

 

More Info

Sergey Levine

UC Berkeley

Keynote Talk: 
Offline Reinforcement Learning

 

 

More Info

Schedule

9:00AM – 5:00 PM

The detailed schedule is now available here

Venue

 

BayLearn 2021 will be an online, Virtual Symposium


#BayLearn2021

BayLearn 2018 will take place at Facebook.

Our Sponsors

BayLearn 2021 is sponsored by the following companies

About BayLearn

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!

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