Stochastic heavy-ball method for constrained stochastic optimization problems

Abstract

In this paper, we consider a heavy-ball method for the constrained stochastic optimization problem by focusing to the situation that the constraint set is specified as the intersection of possibly finitely many constraint sets. A variant algorithm of the stochastic heavy-ball method is proposed which will be incrementally processed by both the stochastic heavy-ball method and random constraint projection simultaneously. They converge almost surely to a solution of the suggested method is exhibited. Finally, a numerical experiment is discussed.