8月21日
研討會, 演講, 講座
MATH - Seminar on Data Science and Applied Math - Towards Better Global Landscape of GAN: How Two Lines of Code Change Makes a Difference
Our understanding of GAN (generative adversarial net) training is still very limited since it is a non-convex-non-concave min-max optimization. As a result, most recent studies focused on local analysis. In this talk, we discuss how to perform a global analysis of GANs.