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Exact and Approximation Algorithms for Clustering
Authors:P. K. Agarwal  C. M. Procopiuc
Affiliation:(1) Center for Geometric Computing, Department of Computer Science, Box 90129, Duke University, Durham, NC 27708-0129, USA. pankaj@cs.duke.edu, magda@research.att.com., US
Abstract:
In this paper we present an n^ O(k 1-1/d ) -time algorithm for solving the k -center problem in reals d , under L fty - and L 2 -metrics. The algorithm extends to other metrics, and to the discrete k -center problem. We also describe a simple (1+ɛ) -approximation algorithm for the k -center problem, with running time O(nlog k) + (k/ɛ)^ O(k 1-1/d ) . Finally, we present an n^ O(k 1-1/d ) -time algorithm for solving the L -capacitated k -center problem, provided that L=Ω(n/k 1-1/d ) or L=O(1) . Received July 25, 2000; revised April 6, 2001.
Keywords:. k -Center clustering   Capacitated clustering   Approximation algorithms.
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