Talk page
Title:
Nonconvex Minimax Optimization
Speaker:
Abstract:
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.
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