Ke Li

Ke Li is broadly interested in machine learning methodology and applications. He is working on a replacement for generative adversarial nets that overcomes mode collapse, a method for automatically discovering new optimization algorithms and a family of randomized algorithms for exact nearest neighbor search that sidesteps dimensionality.