Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
: In this paper, we present an approach for writer identification carried out using off-line Arabic handwriting. Our proposed method is based on the combination of global and struc...
The design of computer architectures requires the setting of multiple parameters on which the final performance depends. The number of possible combinations make an extremely huge ...
Pedro A. Castillo, Antonio Miguel Mora, Juan Juli&...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...