In this paper, we concentrate on a stochastic non-monotone DR-submodular maximization problem over a convex constraint , where the objective function arises as an expectation of a set of stochastic functions. We develop an algorithm named SPIDER-FW, which is a stochastic version of the classical Frank-Wolfe algorithm with (in expectation) approximation guarantee, the best guarantee so far …