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DOI: 10.4230/LIPIcs.APPROX-RANDOM.2017.11
URN: urn:nbn:de:0030-drops-75602
URL: http://drops.dagstuhl.de/opus/volltexte/2017/7560/
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Huang, Chien-Chung ; Kakimura, Naonori ; Yoshida, Yuichi

Streaming Algorithms for Maximizing Monotone Submodular Functions under a Knapsack Constraint

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Abstract

In this paper, we consider the problem of maximizing a monotone submodular function subject to a knapsack constraint in the streaming setting. In particular, the elements arrive sequentially and at any point of time, the algorithm has access only to a small fraction of the data stored in primary memory. For this problem, we propose a (0.363-epsilon)-approximation algorithm, requiring only a single pass through the data; moreover, we propose a (0.4-epsilon)-approximation algorithm requiring a constant number of passes through the data. The required memory space of both algorithms depends only on the size of the knapsack capacity and epsilon.

BibTeX - Entry

@InProceedings{huang_et_al:LIPIcs:2017:7560,
  author =	{Chien-Chung Huang and Naonori Kakimura and Yuichi Yoshida},
  title =	{{Streaming Algorithms for Maximizing Monotone Submodular Functions under a Knapsack Constraint}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2017)},
  pages =	{11:1--11:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-044-6},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{81},
  editor =	{Klaus Jansen and Jos{\'e} D. P. Rolim and David Williamson and Santosh S. Vempala},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2017/7560},
  URN =		{urn:nbn:de:0030-drops-75602},
  doi =		{10.4230/LIPIcs.APPROX-RANDOM.2017.11},
  annote =	{Keywords: submodular functions, single-pass streaming, multiple-pass streaming, constant approximation}
}

Keywords: submodular functions, single-pass streaming, multiple-pass streaming, constant approximation
Seminar: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2017)
Issue Date: 2017
Date of publication: 31.07.2017


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