c86ff2d301940fce9357de92c5222b44-Supplemental-Conference.pdf

Stochastic Gradient Descent (SGD) has been the method of choice for learning large-scale non-convex models. While a general analysis of when SGD works has been elusive, there has been a lot of recent progress in understanding the convergence of Gradient Flow (GF) on the population loss, partly due to the simplicity thatacontinuous-time analysis buysus.