License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ISAAC.2018.46
URN: urn:nbn:de:0030-drops-99942
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/9994/
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Blömer, Johannes ; Brauer, Sascha ; Bujna, Kathrin

Coresets for Fuzzy K-Means with Applications

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Abstract

The fuzzy K-means problem is a popular generalization of the well-known K-means problem to soft clusterings. We present the first coresets for fuzzy K-means with size linear in the dimension, polynomial in the number of clusters, and poly-logarithmic in the number of points. We show that these coresets can be employed in the computation of a (1+epsilon)-approximation for fuzzy K-means, improving previously presented results. We further show that our coresets can be maintained in an insertion-only streaming setting, where data points arrive one-by-one.

BibTeX - Entry

@InProceedings{blmer_et_al:LIPIcs:2018:9994,
  author =	{Johannes Bl{\"o}mer and Sascha Brauer and Kathrin Bujna},
  title =	{{Coresets for Fuzzy K-Means with Applications}},
  booktitle =	{29th International Symposium on Algorithms and Computation  (ISAAC 2018)},
  pages =	{46:1--46:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-094-1},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{123},
  editor =	{Wen-Lian Hsu and Der-Tsai Lee and Chung-Shou Liao},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/9994},
  URN =		{urn:nbn:de:0030-drops-99942},
  doi =		{10.4230/LIPIcs.ISAAC.2018.46},
  annote =	{Keywords: clustering, fuzzy k-means, coresets, approximation algorithms, streaming}
}

Keywords: clustering, fuzzy k-means, coresets, approximation algorithms, streaming
Collection: 29th International Symposium on Algorithms and Computation (ISAAC 2018)
Issue Date: 2018
Date of publication: 06.12.2018

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