Reviews: Continuous-time Models for Stochastic Optimization Algorithms

The paper presents an SDE approximation of mini-batch stochastic gradient descent and stochastic variance reduction gradient descent, two widely used methods, and they derive convergence rates. It presents a nice (i.e., not revolutionary, but still of interest to the community) result that fits within this area. Reviewers have a few suggestions for clarifications/improvements.