Deep learning has become one of the leading methods of machine learning, with significant breakthroughs in the the domains of computer vision and speech recognition, among others. In this talk, I will describe some major obstacles, such as computation time and adversarial attacks, and present a number of possible directions we are taking to overcome these challenges.
Date and Time:
Thursday, January 10, 2019 - 13:30 to 14:30
Speaker:
Etan Fetaya
Location:
C110
Speaker Bio:
Ethan Fetaya is a postdoctoral fellow at the University of Toronto. He received his PhD from the Weizmann Institute, under the supervision of Prof. Shimon Ullman. His research is in machine learning, with applications in computer vision and self-driving cars. He is also interested in the application of machine learning algorithms to graph structured data.