Nonconvex Minimax Optimization

Nonconvex Minimax Optimization - Chi Ji

Chi Jin
Princeton University; Member, School of Mathematics
November 20, 2019

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.