It is well known that among all probabilistic graphical Markov models the class of decomposable models is the most advantageous in the sense that the respective distributions can b...
We consider principal component analysis (PCA) in decomposable Gaussian graphical models. We exploit the prior information in these models in order to distribute its computation. ...
—Modern mobile phones are an appealing platform for pervasive computing applications. However, the complexity of these devices makes it difficult for developers to understand th...
The problem of social capital in context of the online social networks is presented in the paper. Not only the specific elements, which characterize the single person and influence...
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...