Conditional Accelerated Lazy Stochastic Gradient Descent

Guanghui Lan, Sebastian Pokutta, Yi Zhou, Daniel Zink

Abstract: In this work we introduce a conditional accelerated lazy stochastic gradient descent algorithm with optimal number of calls to a stochastic first-order oracle and convergence rate $O(1/\epsilon^2)$...