9  
9 Program Highlights »
Toggle Poster Visibility
Tutorial
Mon Dec 3rd 08:30 -- 10:30 AM @ Room 517 CD
Scalable Bayesian Inference
David Dunson
Tutorial
Mon Dec 3rd 08:30 -- 10:30 AM @ Room 220 CD
Adversarial Robustness: Theory and Practice
J. Zico Kolter · Aleksander Madry
Tutorial
Mon Dec 3rd 08:30 -- 10:30 AM @ Room 220 E
Visualization for Machine Learning
Fernanda Viégas · Martin Wattenberg
Tutorial
Mon Dec 3rd 11:00 AM -- 01:00 PM @ Room 220 E
Common Pitfalls for Studying the Human Side of Machine Learning
Deirdre Mulligan · Nitin Kohli · Joshua A. Kroll
Tutorial
Mon Dec 3rd 11:00 AM -- 01:00 PM @ Rooms 517 CD
Negative Dependence, Stable Polynomials, and All That
Suvrit Sra · Stefanie Jegelka
Tutorial
Mon Dec 3rd 11:00 AM -- 01:00 PM @ Room 220 CD
Unsupervised Deep Learning
Alex Graves · Marc'Aurelio Ranzato
Tutorial
Mon Dec 3rd 02:30 -- 04:30 PM @ Room 220 CD
Automatic Machine Learning
Frank Hutter · Joaquin Vanschoren
Tutorial
Mon Dec 3rd 02:30 -- 04:30 PM @ Room 220 E
Statistical Learning Theory: a Hitchhiker's Guide
John Shawe-Taylor · Omar Rivasplata
Tutorial
Mon Dec 3rd 02:30 -- 04:30 PM @ Room 517 CD
Counterfactual Inference
Susan Athey