PhD Seminar • Artificial Intelligence — Convergence of Gradient Methods on Bilinear Zero-Sum GamesExport this event to calendar

Wednesday, February 10, 2021 — 12:00 PM EST

Please note: This PhD seminar will be given online.

Guojun Zhang, PhD candidate
David R. Cheriton School of Computer Science

Supervisors: Professors Pascal Poupart and Yaoliang Yu

Min-max formulations have attracted great attention in the ML community due to the rise of deep generative models and adversarial methods, while understanding the dynamics of gradient algorithms for solving such formulations has remained a grand challenge. As a first step, we restrict to bilinear zero-sum games and give a systematic analysis of popular gradient updates, for both simultaneous and alternating versions. We provide exact conditions for their convergence and find the optimal parameter setup and convergence rates. In particular, our results offer formal evidence that alternating updates converge “better” than simultaneous ones. 


To join this PhD seminar on Zoom, please go to https://vectorinstitute.zoom.us/j/93656462222?pwd=UXFKRUIvcXZnWjUxNkpBeGcrZnFvQT09.

Location 
Online PhD seminar
200 University Avenue West

Waterloo, ON N2L 3G1
Canada
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