A constant factor approximation algorithm for k-median clustering with outliers

  • Authors:
  • Ke Chen

  • Affiliations:
  • University of Illinois at Urbana-Champaign/ Urbana, IL

  • Venue:
  • Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
  • Year:
  • 2008

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Abstract

We consider the k-median clustering with outliers problem: Given a finite point set in a metric space and parameters k and m, we want to remove m points (called outliers), such that the cost of the optimal k-median clustering of the remaining points is minimized. We present the first polynomial time constant factor approximation algorithm for this problem.