2019-2020 Machine Learning Advances and Applications Seminar
Description
This seminar series is the first formal gathering of academic and industrial data scientists across the Greater Toronto Area (GTA) to discuss advanced topics in machine learning and its goal is to build a stronger machine learning community in Toronto. The talks will be given by international and local faculty and industry professionals.
The seminar series is intended for university faculty and graduate students in machine learning across computer science, ECE, statistics, mathematics, linguistics, and medicine, as well as PhD-level data scientists doing interesting applied research in the GTA.
A large emphasis will be placed on the social aspects of the gathering. The Toronto machine learning community will be stronger when we know each other and know what problems people are working on.
Schedule
12:00 to 13:00 |
Stefanie Jegelka, Massachusetts Institute of Technology |
12:00 to 12:20 |
Angela Schoellig, University of Toronto and Vector Institute |
12:20 to 12:40 |
Animesh Garg, University of Toronto and Vector Institute |
12:40 to 13:00 |
Yaoliang Yu, University of Waterloo and Vector Institute |
13:00 to 13:20 |
Gennady Pekhimenko, University of Toronto and Vector Institute |
12:00 to 13:00 |
Jascha Sohl-Dickstein, Google |
12:00 to 12:15 |
Toni Pitassi, University of Toronto and Vector Institute |
12:15 to 12:30 |
Nicolas Papernot, University of Toronto and Vector Institute |
12:30 to 12:45 |
Bo Wang, University of Toronto and Vector Institute |
12:00 to 13:00 |
Sergey Levine, University of California Berkeley |