Clustering and scheduling of tasks for parallel implementation is a well researched problem. Several techniques have been presented in the literature to improve performance and re...
The clustering algorithm DBSCAN relies on a density-based notion of clusters and is designed to discover clusters of arbitrary shape as well as to distinguish noise. In this paper,...
This paper introduces a novel statistical mixture model for probabilistic grouping of distributional histogram data. Adopting the Bayesian framework, we propose to perform anneale...
We describe imprecise calendars, a way to organize and schedule clusters of nodes in a computation grid. Imprecise calendars permit the easy and efficient sharing of resources bet...
The software clustering problem has attracted much attention recently, since it is an integral part of the process of reverse engineering large software systems. A key problem in ...