A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. Dete...
Classification of texts potentially containing a complex and specific terminology requires the use of learning methods that do not rely on extensive feature engineering. In this w...
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Automata models of learning systems introduced in the 1960s were popularized as learning automata (LA) in a survey paper in 1974 [1]. Since then, there have been many fundamental a...
Biological systems consist of many components and interactions between them. In Systems Biology the principal problem is modeling complex biological systems and reconstructing inte...
Marenglen Biba, Stefano Ferilli, Nicola Di Mauro, ...