资源论文Interlaced Greedy Algorithm for Maximization of Submodular Functions in Nearly Linear Time

Interlaced Greedy Algorithm for Maximization of Submodular Functions in Nearly Linear Time

2020-02-20 | |  50 |   31 |   0

Abstract

A deterministic approximation algorithm is presented for the maximization of non-monotone submodular functions over a ground set of size n subject to cardinality constraint k; the algorithm is based upon the idea of interlacing two greedy procedures. The algorithm uses interlaced,  thresholded greedy procedures to obtain tight ratio 图片.png queries of the objective function, which improves upon both the ratio and the quadratic time complexity of the previously fastest deterministic algorithm for this problem. The algorithm is validated in the context of two applications of non-monotone submodular maximization, on which it outperforms the fastest deterministic and randomized algorithms in prior literature.

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