Background: This study concerns the development of a high performance workflow that, using grid technology, correlates different kinds of Bioinformatics data, starting from the ba...
Ivan Merelli, Giulia Morra, Daniele D'Agostino, An...
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...
We present sparse topical coding (STC), a non-probabilistic formulation of topic models for discovering latent representations of large collections of data. Unlike probabilistic t...
Blogs have the aordance to become an integral part of teaching and learning processes as a vehicle for knowledge management. Open, exible systems integrating blogs provide user-f...
Unsupervised learning of linguistic structure is a difficult problem. A common approach is to define a generative model and maximize the probability of the hidden structure give...