Constrained Submodular Maximization: Beyond 1/e

2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS)(2016)

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摘要
In this work, we present a new algorithm for maximizing a non-monotone submodular function subject to a general constraint. Our algorithm finds an approximate fractional solution for maximizing the multilinear extension of the function over a down-closed polytope. The approximation guarantee is 0.372 and it is the first improvement over the 1/e approximation achieved by the unified Continuous Greedy algorithm [Feldman et al., FOCS 2011].
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关键词
submodular functions,maximization
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