Recent researches have highlighted the importance of developing a network with distributed problem solving abilities thus enhancing reliability with equal share of network resourc...
A crucial issue for Machine Learning and Data Mining is Feature Selection, selecting the relevant features in order to focus the learning search. A relaxed setting for Feature Sele...
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...
Gaussian blurring mean-shift (GBMS) is a nonparametric clustering algorithm, having a single bandwidth parameter that controls the number of clusters. The algorithm iteratively sh...
Due to the strong increase of processing units available to the end user, expressing parallelism of an algorithm is a major challenge for many researchers. Parallel applications ar...