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Document
Coresets for Fuzzy K-Means with Applications

Authors: Johannes Blömer, Sascha Brauer, and Kathrin Bujna

Published in: LIPIcs, Volume 123, 29th International Symposium on Algorithms and Computation (ISAAC 2018)


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.

Cite as

Johannes Blömer, Sascha Brauer, and Kathrin Bujna. Coresets for Fuzzy K-Means with Applications. In 29th International Symposium on Algorithms and Computation (ISAAC 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 123, pp. 46:1-46:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


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@InProceedings{blomer_et_al:LIPIcs.ISAAC.2018.46,
  author =	{Bl\"{o}mer, Johannes and Brauer, Sascha and Bujna, Kathrin},
  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 =	{Hsu, Wen-Lian and Lee, Der-Tsai and Liao, Chung-Shou},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2018.46},
  URN =		{urn:nbn:de:0030-drops-99942},
  doi =		{10.4230/LIPIcs.ISAAC.2018.46},
  annote =	{Keywords: clustering, fuzzy k-means, coresets, approximation algorithms, streaming}
}
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