Advances in Probabilistic Graphical Models

Brings together important topics of research in probabilistic graphical modeling, learning from data and probabilistic inference. This title includes coverage of such topics as the characterization of conditional independence, the learning of graphical models with latent variables, and extensions to the influence diagram formalism.