2017
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy
ICLR 2017poster
We propose a method to optimize the representation and distinguishability of samples from two probability distributions, by maximizing the estimated power of a statistical test based on the maximum mean discrepancy (MMD). This optimized MMD is applied to the setting of unsupervised learning by gener…