Probabilistic Graphical Models : (Record no. 200434077)

MARC details
000 -LEADER
fixed length control field 03835nam a22004695i 4500
001 - CONTROL NUMBER
control field 200434077
003 - CONTROL NUMBER IDENTIFIER
control field TR-AnTOB
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260122094311.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 150619s2015 xxk| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781447166993
Canceled/invalid ISBN 978-1-4471-6699-3
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-1-4471-6699-3
Source of number or code doi
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Description conventions rda
Transcribing agency DLC
Modifying agency TR-AnTOB
041 0# - LANGUAGE CODE
Language code of text/sound track or separate title İngilizce
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA276-280
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYAM
Source bicssc
Subject category code COM077000
Source bisacsh
Subject category code UYAM
Source thema
Subject category code UFM
Source thema005.55
-- 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Sucar, Luis Enrique
Relator term author
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
9 (RLIN) 152020
245 10 - TITLE STATEMENT
Title Probabilistic Graphical Models :
Remainder of title Principles and Applications /
Statement of responsibility, etc. by Luis Enrique Sucar.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture London :
Name of producer, publisher, distributor, manufacturer Springer London :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2015.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource
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
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
490 0# - SERIES STATEMENT
Series statement Advances in Computer Vision and Pattern Recognition,
International Standard Serial Number 2191-6586
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Part I: Fundamentals -- Introduction -- Probability Theory -- Graph Theory -- Part II: Probabilistic Models -- Bayesian Classifiers -- Hidden Markov Models -- Markov Random Fields -- Bayesian Networks: Representation and Inference -- Bayesian Networks: Learning -- Dynamic and Temporal Bayesian Networks -- Part III: Decision Models -- Decision Graphs -- Markov Decision Processes -- Part IV: Relational and Causal Models -- Relational Probabilistic Graphical Models -- Graphical Causal Models.
520 ## - SUMMARY, ETC.
Summary, etc. This accessible text/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes. Topics and features: Presents a unified framework encompassing all of the main classes of PGMs Explores the fundamental aspects of representation, inference and learning for each technique Describes the practical application of the different techniques Examines the latest developments in the field, covering multidimensional Bayesian classifiers, relational graphical models and causal models Provides exercises, suggestions for further reading, and ideas for research or programming projects at the end of each chapter Suggests possible course outlines for instructors in the preface This classroom-tested work is suitable as a textbook for an advanced undergraduate or a graduate course in probabilistic graphical models for students of computer science, engineering, and physics. Professionals wishing to apply probabilistic graphical models in their own field, or interested in the basis of these techniques, will also find the book to be an invaluable reference. Dr. Luis Enrique Sucar is a Senior Research Scientist at the National Institute for Astrophysics, Optics and Electronics (INAOE), Puebla, Mexico.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Artificial intelligence
9 (RLIN) 1543
Topical term or geographic name entry element Pattern recognition systems
9 (RLIN) 1133
Topical term or geographic name entry element Mathematical statistics
9 (RLIN) 496
Topical term or geographic name entry element Electrical engineering
9 (RLIN) 16722
Topical term or geographic name entry element Probabilities
9 (RLIN) 818
655 #0 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books
9 (RLIN) 2032
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
9 (RLIN) 59873
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-1-4471-6699-3">https://doi.org/10.1007/978-1-4471-6699-3</a>
Materials specified Springer eBooks
Public note Online access link to the resource
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type E-Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Not for loan Collection code Home library Current library Date acquired Source of acquisition Coded location qualifier Inventory number Total Checkouts Full call number Barcode Date last seen Date shelved Koha item type
    Library of Congress Classification Geçerli değil-e-Kitap / Not applicable-e-Book E-Kitap Koleksiyonu Merkez Kütüphane Merkez Kütüphane 11/04/2018 Satın Alma / Purchase BİL/ELE/MAT/YAP   QA276-280EBK EBK00766 11/10/2023 11/04/2018 E-Book
Devinim Yazılım Eğitim Danışmanlık tarafından Koha'nın orjinal sürümü uyarlanarak geliştirilip kurulmuştur.