This book brings together important topics of current research
in probabilistic graphical modeling, learning from data and
probabilistic inference. Coverage includes such topics as the
characterization of conditional independence, the learning of
graphical models with latent variables, and extensions to the
influence diagram formalism as well as important application
fields, such as the control of vehicles, bioinformatics and
medicine.
General
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