2020-2021 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.
Register for the next seminar by clicking the following link: https://zoom.us/meeting/register/tJUvdu6tqTojHtduydg9EVFTRlmNjK5_Y02y
Seminars are held on Zoom. You need to register to get a link to join the seminar.
Schedule
| 15:00 to 16:00 |
Shakir Mohamed, DeepMind |
| 15:00 to 16:00 |
Surya Ganguli, Stanford University |
| 15:00 to 16:00 |
Daphne Koller, Stanford University |
| 15:00 to 16:00 |
Percy Liang, Stanford University |
| 15:00 to 16:00 |
Chelsea Finn, Stanford University/Google Brain |
| 15:00 to 16:00 |
Peter Dayan, Max Planck Institute |
| 15:00 to 16:00 |
Moritz Hardt, University of California Berkeley |
| 15:00 to 15:30 |
Jakob Foerster, Facebook |
| 15:30 to 16:00 |
Chris Maddison, University of Toronto |
| 15:00 to 16:00 |
Douglas Eck, Google Research, Brain Team/Magenta |
| 15:00 to 16:00 |
David Lopez-Paz, Facebook |
| 15:00 to 16:00 |
Zico Kolter, Carnegie Mellon University |
| 15:00 to 16:00 |
Sham Kakade, University of Washington |
| 15:00 to 16:00 |
Jason Weston, Facebook |
