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When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.APPROX-RANDOM.2014.96
URN: urn:nbn:de:0030-drops-46907
URL: http://drops.dagstuhl.de/opus/volltexte/2014/4690/
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Crouch, Michael ; Stubbs, Daniel M.

Improved Streaming Algorithms for Weighted Matching, via Unweighted Matching

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Abstract

We present a (4 + epsilon) approximation algorithm for weighted graph matching which applies in the semistreaming, sliding window, and MapReduce models; this single algorithm improves the previous best algorithm in each model. The algorithm operates by reducing the maximum-weight matching problem to a polylog number of copies of the maximum-cardinality matching problem. The algorithm also extends to provide approximation guarantees for the more general problem of finding weighted independent sets in p-systems (which include intersections of p matroids and p-bounded hypergraph matching).

BibTeX - Entry

@InProceedings{crouch_et_al:LIPIcs:2014:4690,
  author =	{Michael Crouch and Daniel M. Stubbs},
  title =	{{Improved Streaming Algorithms for Weighted Matching, via Unweighted Matching}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2014)},
  pages =	{96--104},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-74-3},
  ISSN =	{1868-8969},
  year =	{2014},
  volume =	{28},
  editor =	{Klaus Jansen and Jos{\'e} D. P. Rolim and Nikhil R. Devanur and Cristopher Moore},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2014/4690},
  URN =		{urn:nbn:de:0030-drops-46907},
  doi =		{10.4230/LIPIcs.APPROX-RANDOM.2014.96},
  annote =	{Keywords: Streaming Algorithms, Graph Matching, Weighted Graph Matching, MapReduce, Independence Systems}
}

Keywords: Streaming Algorithms, Graph Matching, Weighted Graph Matching, MapReduce, Independence Systems
Seminar: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2014)
Issue Date: 2014
Date of publication: 02.09.2014


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