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

Video: 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.