Statistics Seminar

Abstract: Nesterov’s accelerated gradient descent algorithm is an optimal method in gradient-based convex optimization. In this talk, we discuss an extension to accelerated stochastic gradient descent with multiplicative noise. This is motivated by applications in overparametrized machine learning. A generalization of Nesterov’s method (AGNES) is introduced, which provably achieves acceleration in the general setting.