Modeling and reasoning with Bayesian networks / (Record no. 121141)

MARC details
000 -LEADER
fixed length control field 03035nam a22003858i 4500
001 - CONTROL NUMBER
control field CR9780511811357
003 - CONTROL NUMBER IDENTIFIER
control field UkCbUP
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20201015164239.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m|||||o||d||||||||
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr||||||||||||
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 101021s2009||||enk o ||1 0|eng|d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780511811357 (ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9780521884389 (hardback)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781107678422 (paperback)
040 ## - CATALOGING SOURCE
Original cataloging agency UkCbUP
Language of cataloging eng
Description conventions rda
Transcribing agency
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA279.5
Item number .D37 2009
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5/42
Edition number 22
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Darwiche, Adnan,
Dates associated with a name 1966-
Relator term author.
245 10 - TITLE STATEMENT
Title Modeling and reasoning with Bayesian networks /
Statement of responsibility, etc. Adnan Darwiche.
246 3# - VARYING FORM OF TITLE
Title proper/short title Modeling & Reasoning with Bayesian Networks
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cambridge :
Name of producer, publisher, distributor, manufacturer Cambridge University Press,
Date of production, publication, distribution, manufacture, or copyright notice 2009.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (xii, 548 pages) :
Other physical details digital, PDF file(s).
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
500 ## - GENERAL NOTE
General note Title from publisher's bibliographic system (viewed on 05 Oct 2015).
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction -- Propositional logic -- Probability calculus -- Bayesian networks -- Building Bayesian networks -- Inference by variable elimination -- Inference by factor elimination -- Inference by conditioning -- Models for graph decomposition -- Most likely instantiations -- The complexity of probabilistic inference -- Compiling Bayesian networks -- Inference with local structure -- Approximate inference by belief propagation -- Approximate inference by stochastic sampling -- Sensitivity analysis -- Learning : the maximum likelihood approach -- Learning : the Bayesian approach.
520 ## - SUMMARY, ETC.
Summary, etc. This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and approximate inference algorithms at both theoretical and practical levels. The treatment of exact algorithms covers the main inference paradigms based on elimination and conditioning and includes advanced methods for compiling Bayesian networks, time-space tradeoffs, and exploiting local structure of massively connected networks. The treatment of approximate algorithms covers the main inference paradigms based on sampling and optimization and includes influential algorithms such as importance sampling, MCMC, and belief propagation. The author assumes very little background on the covered subjects, supplying in-depth discussions for theoretically inclined readers and enough practical details to provide an algorithmic cookbook for the system developer.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Bayesian statistical decision theory
General subdivision Graphic methods.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Inference.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Probabilities.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Modeling.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Print version:
International Standard Book Number 9780521884389
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1017/CBO9780511811357">https://doi.org/10.1017/CBO9780511811357</a>

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