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(14 events)   Timezone: »  
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Tutorial
Mon Dec 03 05:30 AM -- 07:30 AM (PST) @ Room 220 E
Visualization for Machine Learning
Fernanda ViĆ©gas · Martin Wattenberg
Tutorial
Mon Dec 03 05:30 AM -- 07:30 AM (PST) @ Room 220 CD
Adversarial Robustness: Theory and Practice
J. Zico Kolter · Aleksander Madry
Tutorial
Mon Dec 03 05:30 AM -- 07:30 AM (PST) @ Room 517 CD
Scalable Bayesian Inference
David Dunson
Tutorial
Mon Dec 03 08:00 AM -- 10:00 AM (PST) @ Room 220 CD
Unsupervised Deep Learning
Alex Graves · Marc'Aurelio Ranzato
Tutorial
Mon Dec 03 08:00 AM -- 10:00 AM (PST) @ Room 517 CD
Negative Dependence, Stable Polynomials, and All That
Suvrit Sra · Stefanie Jegelka
Tutorial
Mon Dec 03 08:00 AM -- 10:00 AM (PST) @ Room 220 E
Common Pitfalls for Studying the Human Side of Machine Learning
Deirdre Mulligan · Nitin Kohli · Joshua Kroll
Break
Mon Dec 03 10:30 AM -- 11:00 AM (PST)
Coffee Break
Tutorial
Mon Dec 03 11:30 AM -- 01:30 PM (PST) @ Room 220 E
Statistical Learning Theory: a Hitchhiker's Guide
John Shawe-Taylor · Omar Rivasplata
Tutorial
Mon Dec 03 11:30 AM -- 01:30 PM (PST) @ Room 517 CD
Counterfactual Inference
Susan Athey
Tutorial
Mon Dec 03 11:30 AM -- 01:30 PM (PST) @ Room 220 CD
Automatic Machine Learning
Frank Hutter · Joaquin Vanschoren
Invited Talk
Mon Dec 03 02:30 PM -- 03:20 PM (PST) @ Room 220 CD
Accountability and Algorithmic Bias: Why Diversity and Inclusion Matters
Laura Gomez
Break
Mon Dec 03 04:30 PM -- 05:00 PM (PST)
Coffee Break
Break
Mon Dec 03 05:00 PM -- 05:30 PM (PST)
Opening Remarks
Break
Mon Dec 03 06:30 PM -- 08:30 PM (PST)
Opening Reception