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Librería: ThriftBooks-Atlanta, AUSTELL, GA, Estados Unidos de America
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Añadir al carritoHardcover. Condición: Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
Librería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de America
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Librería: Books Puddle, New York, NY, Estados Unidos de America
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Librería: Anybook.com, Lincoln, Reino Unido
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Añadir al carritoCondición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:9783540689942.
Librería: SMASS Sellers, IRVING, TX, Estados Unidos de America
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Librería: UK BOOKS STORE, London, LONDO, Reino Unido
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Añadir al carritoCondición: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 115,42
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Idioma: Inglés
Publicado por Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2007
ISBN 10: 354068994X ISBN 13: 9783540689942
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Librería: UK BOOKS STORE, London, LONDO, Reino Unido
EUR 170,90
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Añadir al carritoHardcover. Condición: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-12 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Librería: Mispah books, Redhill, SURRE, Reino Unido
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Añadir al carritoHardcover. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 44,61
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Añadir al carritoCondición: New. pp. x + 396 Illus. This item is printed on demand.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg Feb 2007, 2007
ISBN 10: 354068994X ISBN 13: 9783540689942
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 106,99
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 396 pp. Englisch.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg, 2007
ISBN 10: 354068994X ISBN 13: 9783540689942
Librería: moluna, Greven, Alemania
EUR 92,27
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Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the state of the art in probabilistic graphical models, Includes carefully edited and reviewed surveys and research articlesThis book brings together important topics of current research in probabilistic graphical modeling, lea.
Librería: preigu, Osnabrück, Alemania
EUR 95,70
Cantidad disponible: 5 disponibles
Añadir al carritoBuch. Condición: Neu. Advances in Probabilistic Graphical Models | Peter Lucas (u. a.) | Buch | Studies in Fuzziness and Soft Computing | x | Englisch | 2007 | Springer | EAN 9783540689942 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Idioma: Inglés
Publicado por Springer, Springer Feb 2007, 2007
ISBN 10: 354068994X ISBN 13: 9783540689942
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 conditionalindependence, 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 396 pp. Englisch.