Seminar on Theoretical Machine Learning

Topic: Nonconvex Minimax Optimization

Speaker: Chi Jin

Affiliation: Princeton University; Member, School of Mathematics

Date & Time: Wednesday November 20th, 2019, 12:00pm - 1:30pm

Location: Dilworth Room


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.