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Abstract: We give polynomial time approximation schemes for the problem of partitioning an input set of n points into a fixed number k of clusters so as to minimize the sum over all clusters of the total pairwise distances in a cluster. Our algorithms work for arbitrary metric spaces as well as for points in R^d where the distance between two points x; y is measured by kx yk 2 (notice that (R ; k k 2 ) is not a metric space). Our algorithms can be modified to handle other objective functions, such as... (Update)
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BibTeX entry: (Update)
W. F. de la Vega, M. Karpinski, C. Kenyon, and Y. Rabani, Polynomial time approximation schemes for metric min-sum clustering, Tech. Rep. 25, Electronic Colloquium on Computational COmplexity, 2002. http://citeseer.ist.psu.edu/fernandezdelavega02polynomial.html More
@article{ vega02polynomial,
author = "Wenceslas Fernandez de la Vega and Marek Karpinski and Claire Kenyon and Yuval Rabani",
title = "Polynomial Time Approximation Schemes for Metric Min-Sum Clustering",
journal = "Electronic Colloquium on Computational Complexity (ECCC)",
number = "025",
year = "2002",
url = "citeseer.ist.psu.edu/fernandezdelavega02polynomial.html" }
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