Overcoming Mode Collapse and the Curse of Dimensionality

Machine Learning Lecture at CMU by Ke Li, Ph.D. Candidate at the University of California, Berkeley Lecturer: Ke Li Carnegie Mellon University Abstract: In this talk, Li presents his team’s work on overcoming two long-standing problems in machine learning and algorithms: 1. Mode collapse in generative adversarial nets (GANs) Generative adversarial nets (GANs) are perhaps the most popular class of generative models in use today. Unfortunately, they suffer from the well-documented problem of mode coll