Huge amounts of data are stored in autonomous, geographically distributed sources. The discovery of previously unknown, implicit and valuable knowledge is a key aspect of the expl...
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...
distributed shared-memory (SDSM) provides the abstraction necessary to run shared-memory applications on cost-effective parallel platforms such as clusters of workstations. Howeve...
1 We present an approach to schedulability analysis for the synthesis of multi-cluster distributed embedded systems consisting of timetriggered and event-triggered clusters, interc...
A novel approach to combining clustering and feature selection is presented. It implements a wrapper strategy for feature selection, in the sense that the features are directly se...