Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap

5 Nov 2017Aryan MokhtariHamed HassaniAmin Karbasi

In this paper, we study the problem of \textit{constrained} and \textit{stochastic} continuous submodular maximization. Even though the objective function is not concave (nor convex) and is defined in terms of an expectation, we develop a variant of the conditional gradient method, called \alg, which achieves a \textit{tight} approximation guarantee... (read more)

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