Advances in Probabilistic Graphical Models: 213 (Studies in Fuzziness and Soft Computing) - Hardcover

 
9783540689942: Advances in Probabilistic Graphical Models: 213 (Studies in Fuzziness and Soft Computing)
Hardcover
ISBN 10: 354068994X ISBN 13: 9783540689942
Verlag: Springer, 2007

Inhaltsangabe

In recent years considerable progress has been made in the area of probabilistic graphical models, in particular Bayesian networks and influence diagrams. Probabilistic graphical models have become mainstream in the area of uncertainty in artificial intelligence;
contributions to the area are coming from computer science, mathematics, statistics and engineering.

This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional
independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Von der hinteren Coverseite

In recent years considerable progress has been made in the area of probabilistic graphical models, in particular Bayesian networks and influence diagrams. Probabilistic graphical models have become mainstream in the area of uncertainty in artificial intelligence;
contributions to the area are coming from computer science, mathematics, statistics and engineering.

This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional
independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism.  In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
Springer
Erscheinungsdatum
2007
Sprache
Englisch
ISBN 10 
354068994X
ISBN 13 
9783540689942
Einband
Tapa dura
Anzahl der Seiten
396
Herausgeber
Salmerón Cerdan Antonio, Gámez José A., Lucas Peter
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
CMN Printpool Inh. Mathis Neumann
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

Friedrich-Karl-Str. 9
Hamburg
Deutschland

Weitere beliebte Ausgaben desselben Titels

9783642088544: Advances in Probabilistic Graphical Models: 213 (Studies in Fuzziness and Soft Computing)

Vorgestellte Ausgabe

ISBN 10:  3642088546 ISBN 13:  9783642088544
Verlag: Springer, 2010
Softcover