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Advances in Probabilistic Graphical Models by Dr. Lucas, Peter: New

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Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
Book Title
Advances in Probabilistic Graphical Models
Publication Date
2007-02-05
Pages
386
ISBN
9783540689942
Subject Area
Computers, Mathematics
Publication Name
Advances in Probabilistic Graphical Models
Publisher
Springer Berlin / Heidelberg
Item Length
9.3 in
Subject
Probability & Statistics / Stochastic Processes, Probability & Statistics / General, Neural Networks, Intelligence (Ai) & Semantics, Applied, Probability & Statistics / Bayesian Analysis, Discrete Mathematics
Publication Year
2007
Series
Studies in Fuzziness and Soft Computing Ser.
Type
Textbook
Format
Hardcover
Language
English
Author
José A. Gámez
Item Weight
26.7 Oz
Item Width
6.1 in
Number of Pages
X, 386 Pages

About this product

Product Information

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.

Product Identifiers

Publisher
Springer Berlin / Heidelberg
ISBN-10
354068994x
ISBN-13
9783540689942
eBay Product ID (ePID)
25038398178

Product Key Features

Number of Pages
X, 386 Pages
Language
English
Publication Name
Advances in Probabilistic Graphical Models
Publication Year
2007
Subject
Probability & Statistics / Stochastic Processes, Probability & Statistics / General, Neural Networks, Intelligence (Ai) & Semantics, Applied, Probability & Statistics / Bayesian Analysis, Discrete Mathematics
Type
Textbook
Subject Area
Computers, Mathematics
Author
José A. Gámez
Series
Studies in Fuzziness and Soft Computing Ser.
Format
Hardcover

Dimensions

Item Weight
26.7 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2006-939264
Dewey Edition
22
Series Volume Number
213
Number of Volumes
1 Vol.
Illustrated
Yes
Dewey Decimal
519.5/42
Lc Classification Number
Qa273.A1-274.9
Table of Content
Foundations.- Markov Equivalence in Bayesian Networks.- A Causal Algebra for Dynamic Flow Networks.- Graphical and Algebraic Representatives of Conditional Independence Models.- Bayesian Network Models with Discrete and Continuous Variables.- Sensitivity Analysis of Probabilistic Networks.- Inference.- A Review on Distinct Methods and Approaches to Perform Triangulation for Bayesian Networks.- Decisiveness in Loopy Propagation.- Lazy Inference in Multiply Sectioned Bayesian Networks Using Linked Junction Forests.- Learning.- A Study on the Evolution of Bayesian Network Graph Structures.- Learning Bayesian Networks with an Approximated MDL Score.- Learning of Latent Class Models by Splitting and Merging Components.- Decision Processes.- An Efficient Exhaustive Anytime Sampling Algorithm for Influence Diagrams.- Multi-currency Influence Diagrams.- Parallel Markov Decision Processes.- Applications.- Applications of HUGIN to Diagnosis and Control of Autonomous Vehicles.- Biomedical Applications of Bayesian Networks.- Learning and Validating Bayesian Network Models of Gene Networks.- The Role of Background Knowledge in Bayesian Classification.
Copyright Date
2007

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