In this paper we describe a general grouping technique to devise faster and simpler approximation schemes for several scheduling problems. We illustrate the technique on two diff...
Aleksei V. Fishkin, Klaus Jansen, Monaldo Mastroli...
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...
Clustering ensembles has been recently recognized as an emerging approach to provide more robust solutions to the data clustering problem. Current methods of clustering ensembles ...
In this paper we study the k-means clustering problem. It is well-known that the general version of this problem is NP-hard. Numerous approximation algorithms have been proposed fo...
Three methods for combining multiple clustering systems are presented and evaluated, focusing on the problem of finding the correspondence between clusters of different systems. ...