Non-submodular maximization on massive data streams

Yijing Wang, Dachuan Xu, Yishui Wang and Dongmei Zhang ()
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Yijing Wang: Beijing University of Technology
Dachuan Xu: Beijing University of Technology
Yishui Wang: Chinese Academy of Sciences
Dongmei Zhang: Shandong Jianzhu University

Journal of Global Optimization, 2020, vol. 76, issue 4, No 5, 729-743

Abstract: Abstract The problem of maximizing a normalized monotone non-submodular set function subject to a cardinality constraint arises in the context of extracting information from massive streaming data. In this paper, we present four streaming algorithms for this problem by utilizing the concept of diminishing-return ratio. We analyze these algorithms to obtain the corresponding approximation ratios, which generalize the previous results for the submodular case. The numerical experiments show that our algorithms have better solution quality and competitive running time when compared to an existing algorithm.

Keywords: Streaming algorithm; Non-submodular maximization; Cardinality constraint; Set function (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10898-019-00840-8

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