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(14 events)   Time zone: Conference local time zone  
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Tutorial
Mon Dec 03 08:30 AM -- 10:30 AM (EST) @ Room 517 CD
Scalable Bayesian Inference
In Tutorials Session 1
David Dunson
Tutorial
Mon Dec 03 08:30 AM -- 10:30 AM (EST) @ Room 220 CD
Adversarial Robustness: Theory and Practice
In Tutorials Session 1
J. Zico Kolter · Aleksander Madry
Tutorial
Mon Dec 03 08:30 AM -- 10:30 AM (EST) @ Room 220 E
Visualization for Machine Learning
In Tutorials Session 1
Fernanda Viégas · Martin Wattenberg
Tutorial
Mon Dec 03 11:00 AM -- 01:00 PM (EST) @ Room 220 CD
Unsupervised Deep Learning
In Tutorials Session 2
Alex Graves · Marc'Aurelio Ranzato
Tutorial
Mon Dec 03 11:00 AM -- 01:00 PM (EST) @ Room 517 CD
Negative Dependence, Stable Polynomials, and All That
In Tutorials Session 2
Suvrit Sra · Stefanie Jegelka
Tutorial
Mon Dec 03 11:00 AM -- 01:00 PM (EST) @ Room 220 E
Common Pitfalls for Studying the Human Side of Machine Learning
In Tutorials Session 2
Deirdre Mulligan · Nitin Kohli · Joshua Kroll
Break
Mon Dec 03 01:30 PM -- 02:00 PM (EST)
Coffee Break
Tutorial
Mon Dec 03 02:30 PM -- 04:30 PM (EST) @ Room 220 CD
Automatic Machine Learning
In Tutorials Session 3
Frank Hutter · Joaquin Vanschoren
Tutorial
Mon Dec 03 02:30 PM -- 04:30 PM (EST) @ Room 517 CD
Counterfactual Inference
In Tutorials Session 3
Susan Athey
Tutorial
Mon Dec 03 02:30 PM -- 04:30 PM (EST) @ Room 220 E
Statistical Learning Theory: a Hitchhiker's Guide
In Tutorials Session 3
John Shawe-Taylor · Omar Rivasplata
Invited Talk
Mon Dec 03 05:30 PM -- 06:20 PM (EST) @ Room 220 CD
Accountability and Algorithmic Bias: Why Diversity and Inclusion Matters
Laura Gomez
Break
Mon Dec 03 07:30 PM -- 08:00 PM (EST)
Coffee Break
Break
Mon Dec 03 08:00 PM -- 08:30 PM (EST)
Opening Remarks
Break
Mon Dec 03 09:30 PM -- 11:30 PM (EST)
Opening Reception