Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Combining classifier methods have shown their effectiveness in a number of applications. Nonetheless, using simultaneously multiple classifiers may result in some cases in a reduc...
Claudio De Stefano, Francesco Fontanella, Alessand...
Social networks have small-world property, hierarchical community structure, and some other properties. This paper proposes models of networks with these properties and algorithm ...
Scalability is a crucial factor in performance evaluation and analysis of parallel and distributed systems. Much effort has been devoted to scalability research and several metric...
In this paper we propose a new distributed learning method called distributed network boosting (DNB) algorithm for distributed applications. The learned hypotheses are exchanged b...