As commodity microprocessors and networks reach performance levels comparable to those used in massively parallel processors, clusters of symmetric multiprocessors are starting to...
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
In this paper, a new fuzzy clustering algorithm that uses cellular learning automata based evolutionary computing (CLA-EC) is proposed. The CLA-EC is a model obtained by combining...
Reza Rastegar, A. R. Arasteh, Arash Hariri, Mohamm...
—Two strategies of distribution of computations can be used to implement parallel solvers for dense linear algebra problems for Heterogeneous Computational Clusters of Multicore ...
—In this paper, we present three different methods for implementing the Probabilistic Neural Network on a Beowulf cluster computer. The three methods, Parallel Full Training Set ...
Jimmy Secretan, Michael Georgiopoulos, Ian Maidhof...