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2002

A Constant-Factor Approximation Algorithm for the k-Median Problem

8 years 11 months ago
A Constant-Factor Approximation Algorithm for the k-Median Problem
We present the first constant-factor approximation algorithm for the metric k-median problem. The k-median problem is one of the most well-studied clustering problems, i.e., those problems in which the aim is to partition a given set of points into clusters so that the points within a cluster are relatively close with respect to some measure. For the metric k-median problem, we are given n points in a metric space. We select k of these to be cluster centers, and then assign each point to its closest selected center. If point j is assigned to a center i, the cost incurred is proportional to the distance between i and j. The goal is to select the k centers that minimize the sum of the assignment costs. We give a 62 3 -approximation algorithm for this problem. This improves upon the best previously known result of O(log k log log k), which was obtained by refining and derandomizing a randomized O(log n log log n)-approximation algorithm of Bartal.
Moses Charikar, Sudipto Guha, Éva Tardos, D
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 2002
Where JCSS
Authors Moses Charikar, Sudipto Guha, Éva Tardos, David B. Shmoys
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