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Fully Dynamic k-Means Coreset in Near-Optimal Update Time

Authors: Max Dupré la Tour, Monika Henzinger, and David Saulpic

Published in: LIPIcs, Volume 308, 32nd Annual European Symposium on Algorithms (ESA 2024)


Abstract
We study in this paper the problem of maintaining a solution to k-median and k-means clustering in a fully dynamic setting. To do so, we present an algorithm to efficiently maintain a coreset, a compressed version of the dataset, that allows easy computation of a clustering solution at query time. Our coreset algorithm has near-optimal update time of Õ(k) in general metric spaces, which reduces to Õ(d) in the Euclidean space ℝ^d. The query time is O(k²) in general metrics, and O(kd) in ℝ^d. To maintain a constant-factor approximation for k-median and k-means clustering in Euclidean space, this directly leads to an algorithm with update time Õ(d), and query time Õ(kd + k²). To maintain a O(polylog k)-approximation, the query time is reduced to Õ(kd).

Cite as

Max Dupré la Tour, Monika Henzinger, and David Saulpic. Fully Dynamic k-Means Coreset in Near-Optimal Update Time. In 32nd Annual European Symposium on Algorithms (ESA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 308, pp. 100:1-100:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{latour_et_al:LIPIcs.ESA.2024.100,
  author =	{la Tour, Max Dupr\'{e} and Henzinger, Monika and Saulpic, David},
  title =	{{Fully Dynamic k-Means Coreset in Near-Optimal Update Time}},
  booktitle =	{32nd Annual European Symposium on Algorithms (ESA 2024)},
  pages =	{100:1--100:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-338-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{308},
  editor =	{Chan, Timothy and Fischer, Johannes and Iacono, John and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2024.100},
  URN =		{urn:nbn:de:0030-drops-211716},
  doi =		{10.4230/LIPIcs.ESA.2024.100},
  annote =	{Keywords: clustering, fully-dynamic, coreset, k-means}
}
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