Reviews: Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection

Overall I think this paper raises an interesting perspective to understanding adversarial generative models. I think this paper has some value by raising the question and offering some interesting experimental results. The theory is quite standard, the authors first cite a relationship between differential privacy and RO stability, then cite that RO stability bounds the generalization gap. The short coming is that the theory only analyzes the discriminator, which do not seem much different compared to previous work analyzing classifiers. It would be much more interesting and novel to see an analysis of the joint learning process of generator and discriminator.