Nonconvex Minimax Optimization

Seminar on Theoretical Machine Learning
Topic:Nonconvex Minimax Optimization
Speaker:Chi Jin
Affiliation:Princeton University; Member, School of Mathematics
Date:Wednesday, November 20
Time/Room:12:00pm - 1:30pm/Dilworth Room
Video Link:https://video.ias.edu/machinelearning/2019/1120-ChiJin

Minimax optimization, especially in its general nonconvex formulation, has found extensive applications in modern machine learning, in settings such as generative adversarial networks (GANs) and adversarial training. It brings a series of unique challenges in addition to those that already persist in nonconvex minimization problems. This talk will cover a set of new phenomena, open problems, and recent results in this emerging field.