License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
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DOI: 10.4230/LIPIcs.ESA.2022.47
URN: urn:nbn:de:0030-drops-169858
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Eiben, Eduard ; Ganian, Robert ; Kanj, Iyad ; Ordyniak, Sebastian ; Szeider, Stefan

Finding a Cluster in Incomplete Data

LIPIcs-ESA-2022-47.pdf (0.7 MB)


We study two variants of the fundamental problem of finding a cluster in incomplete data. In the problems under consideration, we are given a multiset of incomplete d-dimensional vectors over the binary domain and integers k and r, and the goal is to complete the missing vector entries so that the multiset of complete vectors either contains (i) a cluster of k vectors of radius at most r, or (ii) a cluster of k vectors of diameter at most r. We give tight characterizations of the parameterized complexity of the problems under consideration with respect to the parameters k, r, and a third parameter that captures the missing vector entries.

BibTeX - Entry

  author =	{Eiben, Eduard and Ganian, Robert and Kanj, Iyad and Ordyniak, Sebastian and Szeider, Stefan},
  title =	{{Finding a Cluster in Incomplete Data}},
  booktitle =	{30th Annual European Symposium on Algorithms (ESA 2022)},
  pages =	{47:1--47:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-247-1},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{244},
  editor =	{Chechik, Shiri and Navarro, Gonzalo and Rotenberg, Eva and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-169858},
  doi =		{10.4230/LIPIcs.ESA.2022.47},
  annote =	{Keywords: Parameterized complexity, incomplete data, clustering}

Keywords: Parameterized complexity, incomplete data, clustering
Collection: 30th Annual European Symposium on Algorithms (ESA 2022)
Issue Date: 2022
Date of publication: 01.09.2022

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