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MASCLE Machine Learning Seminar: Jacob Abernethy (Georgia Tech) - Building Algorithms by Playing Games
Tue, Feb 26, 2019 @ 04:00 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Jacob Abernethy, Georgia Institute of Technology
Talk Title: Building Algorithms by Playing Games
Series: Visa Research Machine Learning Seminar Series hosted by USC Machine Learning Center
Abstract: A very popular trick for solving certain types of optimization problems is this: write your objective as the solution of a two-player zero-sum game, endow both players with an appropriate learning algorithm, watch how the opponents compete, and extract an (approximate) solution from the actions/decisions taken by the players throughout the process. This approach is very generic and provides a natural template to produce new and interesting algorithms. I will describe this framework and show how it applies in several scenarios, and describe recent work that draws a connection to the Frank-Wolfe algorithm and Nesterov's Accelerated Gradient Descent.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Jacob Abernethy is an Assistant Professor in Computer Science at Georgia Tech. He started his faculty career in the Department of Electrical Engineering and Computer Science at the University of Michigan. In October 2011 he finished a PhD in the Division of Computer Science at the University of California at Berkeley, and then spent nearly two years as a Simons postdoctoral fellow at the CIS department at UPenn. Abernethy's primary interest is in Machine Learning, with a particular focus in sequential decision making, online learning, online algorithms and adversarial learning models.
Host: Haipeng Luo
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department