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Description - Learning in Graphical Models by Michael I. Jordan

Graphical models, a marriage between probability theory and graph theory, provide a natural tool for dealing with two problems that occur throughout applied mathematics and engineering - uncertainty and complexity. This book presents an exploration of issues related to learning within the graphical model formalism. Four chapters are tutorial chapters: inference for Bayesian networks; Monte Carlo methods; variational methods; and learning with Bayesian networks. The remaining chapters cover a range of topics.

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Book Details

ISBN: 9780262600323
ISBN-10: 0262600323
Format: Paperback
(254mm x 178mm x 32mm)
Pages: 644
Imprint: Bradford Books
Publisher: MIT Press Ltd
Publish Date: 20-Jan-1999
Country of Publication: United States

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Author Biography - Michael I. Jordan

Michael I. Jordan is Professor of Computer Science and of Statistics at the University of California, Berkeley, and recipient of the ACM/AAAI Allen Newell Award.

Books By Michael I. Jordan

Graphical Models by Michael I. Jordan
Paperback, October 2001