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...
The recent movement by major Web services towards making many application programming interfaces (APIs) available for public use has led to the development of the new MashUp techno...
Andreas Auinger, Martin Ebner, Dietmar Nedbal, And...
In this paper we propose the CTS (Concious Tutoring System) technology, a biologically plausible cognitive agent based on human brain functions.This agent is capable of learning a...
Usef Faghihi, Philippe Fournier-Viger, Roger Nkamb...
Supervised learners can be used to automatically classify many types of spatially distributed data. For example, land cover classification by hyperspectral image data analysis is ...
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...