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Generalized Center Problems with Outliers

Authors Deeparnab Chakrabarty, Maryam Negahbani

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Deeparnab Chakrabarty
  • Department of Computer Science, Dartmouth College, 9 Maynard St, Hanover, NH, USA , https://web.cs.dartmouth.edu/people/deeparnab-chakrabarty
Maryam Negahbani
  • Department of Computer Science, Dartmouth College, 9 Maynard St, Hanover, NH, USA

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Deeparnab Chakrabarty and Maryam Negahbani. Generalized Center Problems with Outliers. In 45th International Colloquium on Automata, Languages, and Programming (ICALP 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 107, pp. 30:1-30:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.ICALP.2018.30

Abstract

We study the F-center problem with outliers: given a metric space (X,d), a general down-closed family F of subsets of X, and a parameter m, we need to locate a subset S in F of centers such that the maximum distance among the closest m points in X to S is minimized. Our main result is a dichotomy theorem. Colloquially, we prove that there is an efficient 3-approximation for the F-center problem with outliers if and only if we can efficiently optimize a poly-bounded linear function over F subject to a partition constraint. One concrete upshot of our result is a polynomial time 3-approximation for the knapsack center problem with outliers for which no (true) approximation algorithm was known.

Subject Classification

ACM Subject Classification
  • Theory of computation → Facility location and clustering
Keywords
  • Approximation Algorithms
  • Clustering
  • k-Center Problem

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