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Probabilistic Conditional Independence Structures (Hb) Hardback - 2005
by Milan Studeny
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Details
- Title Probabilistic Conditional Independence Structures (Hb)
- Author Milan Studeny
- Binding Hardback
- Edition U. S. EDITION
- Condition New
- Pages 285
- Volumes 1
- Language ENG
- Publisher Springer
- Publication date 2005-01-07
- Illustrated Yes
- Features Bibliography, Illustrated, Index, Table of Contents
- Bookseller's Inventory # BIBNN-76674
- ISBN 9781852338916 / 1852338911
- Weight 1.21 lbs (0.55 kg)
- Dimensions 9.46 x 6.5 x 0.74 in (24.03 x 16.51 x 1.88 cm)
- Category Mathematics
- Library of Congress subjects Decision making - Mathematical models, Distribution (Probability theory)
- Library of Congress Catalogue Number 2004059834
- Dewey Decimal Code 519.5
- Quantity available 5
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From the publisher
First line
From the rear cover
Conditional independence is a topic that lies between statistics and artificial intelligence. Probabilistic Conditional Independence Structures provides the mathematical description of probabilistic conditional independence structures; the author uses non-graphical methods of their description, and takes an algebraic approach.
The monograph presents the methods of structural imsets and supermodular functions, and deals with independence implication and equivalence of structural imsets. Motivation, mathematical foundations and areas of application are included, and a rough overview of graphical methods is also given. In particular, the author has been careful to use suitable terminology, and presents the work so that it will be understood by both statisticians, and by researchers in artificial intelligence. The necessary elementary mathematical notions are recalled in an appendix.
Probabilistic Conditional Independence Structures will be a valuable new addition to the literature, and will interest applied mathematicians, statisticians, informaticians, computer scientists and probabilists with an interest in artificial intelligence. The book may also interest pure mathematicians as open problems are included.
Milan Studen is a senior research worker at the Academy of Sciences of the Czech Republic.
