Abstract— We have used measurements taken on real network to enhance the performance of our radio network planning tool. A distribution learning technique is adopted to realize t...
In this work we present a novel method to model instance-level constraints within a clustering algorithm. Thereby, both similarity and dissimilarity constraints can be used coeval...
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
We argue that K–means and deterministic annealing algorithms for geometric clustering can be derived from the more general Information Bottleneck approach. If we cluster the ide...
There are lots of validation indexes and techniques to study clustering results. Biclustering algorithms have been applied in Systems Biology, principally in DNA Microarray analysi...