Mini-batch Submodular Maximization
Keywords: Submodular maximization, mini-batch
TL;DR: We introduce a mini-batch algorithm for maximizing decomposable submodular functions that significantly improves over sparsifier based approaches.
Abstract: We present the first *mini-batch* algorithm for maximizing a non-negative monotone *decomposable* submodular function, $F=\sum_{i=1}^N f^i$, under a set of constraints. The expected number of oracle evaluations of our algorithm only depends on the size of the ground set. Previous results require a number of oracle evaluations that either depend on $N$ or have a worst-case *exponential* dependence on the size of the ground set.
Primary Area: optimization
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Submission Number: 786
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