Hulu Beijing
Hulu Beijing
Feb 1, 2018 · Artificial Intelligence

Understanding GANs: Theory, Minimax Game, and Training Challenges

This article introduces Generative Adversarial Networks (GANs), explains their minimax formulation, value function, Jensen‑Shannon divergence, common variants, and practical training issues such as gradient saturation, while also previewing the next topic on Hidden Markov Models.

GANGenerative Adversarial NetworksMinimax Game
0 likes · 11 min read
Understanding GANs: Theory, Minimax Game, and Training Challenges