paperback. Condizione: Very Good.
Da: Ria Christie Collections, Uxbridge, Regno Unito
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Da: Ria Christie Collections, Uxbridge, Regno Unito
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Da: Chiron Media, Wallingford, Regno Unito
EUR 56,96
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Aggiungi al carrelloPF. Condizione: New.
Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 59,93
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Aggiungi al carrelloCondizione: New.
Condizione: New. pp. 292.
Da: Antiquariat Bookfarm, Löbnitz, Germania
EUR 43,20
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Aggiungi al carrelloSoftcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. C-04205 9783540225720 Sprache: Englisch Gewicht in Gramm: 550.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 53,49
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Statistical learning theory is aimed at analyzing complex data with necessarily approximate models. This book is intended for an audience with a graduate background in probability theory and statistics. It will be useful to any reader wondering why it may be a good idea, to use asis often done in practice a notoriously 'wrong'' (i.e. over-simplified) model to predict, estimate or classify. This point of view takes its roots in three fields: information theory, statistical mechanics, and PAC-Bayesian theorems. Results on the large deviations of trajectories of Markov chains with rare transitions are also included. They are meant to provide a better understanding of stochastic optimization algorithms of common use in computing estimators. The author focuses on non-asymptotic bounds of the statistical risk, allowing one to choose adaptively between rich and structured families of models and corresponding estimators. Two mathematical objects pervade the book: entropy and Gibbs measures. The goal is to show how to turn them into versatile and efficient technical tools,that will stimulate further studies and results.
paperback. Condizione: New. In shrink wrap. Looks like an interesting title!
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 117,00
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 107,46
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Aggiungi al carrelloPaperback. Condizione: Like New. Like New. book.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 137,80
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Springer Berlin Heidelberg Aug 2004, 2004
ISBN 10: 3540225722 ISBN 13: 9783540225720
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 53,49
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Statistical learning theory is aimed at analyzing complex data with necessarily approximate models. This book is intended for an audience with a graduate background in probability theory and statistics. It will be useful to any reader wondering why it may be a good idea, to use asis often done in practice a notoriously 'wrong'' (i.e. over-simplified) model to predict, estimate or classify. This point of view takes its roots in three fields: information theory, statistical mechanics, and PAC-Bayesian theorems. Results on the large deviations of trajectories of Markov chains with rare transitions are also included. They are meant to provide a better understanding of stochastic optimization algorithms of common use in computing estimators. The author focuses on non-asymptotic bounds of the statistical risk, allowing one to choose adaptively between rich and structured families of models and corresponding estimators. Two mathematical objects pervade the book: entropy and Gibbs measures. The goal is to show how to turn them into versatile and efficient technical tools,that will stimulate further studies and results. 292 pp. Englisch.
Da: Majestic Books, Hounslow, Regno Unito
EUR 77,66
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand pp. 292 Illus.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 78,10
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 292.
Lingua: Inglese
Editore: Springer Berlin Heidelberg, 2004
ISBN 10: 3540225722 ISBN 13: 9783540225720
Da: moluna, Greven, Germania
EUR 48,37
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Aggiungi al carrelloKartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Statistical learning theory is aimed at analyzing complex data with necessarily approximate models. This book is intended for an audience with a graduate background in probability theory and statistics. It will be useful to any reader wondering why it ma.
Lingua: Inglese
Editore: Springer, Springer Vieweg Aug 2004, 2004
ISBN 10: 3540225722 ISBN 13: 9783540225720
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 53,49
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Statistical learning theory is aimed at analyzing complex data with necessarily approximate models. This book is intended for an audience with a graduate background in probability theory and statistics. It will be useful to any reader wondering why it may be a good idea, to use as is often done in practice a notoriously 'wrong'' (i.e. over-simplified) model to predict, estimate or classify. This point of view takes its roots in three fields: information theory, statistical mechanics, and PAC-Bayesian theorems. Results on the large deviations of trajectories of Markov chains with rare transitions are also included. They are meant to provide a better understanding of stochastic optimization algorithms of common use in computing estimators. The author focuses on non-asymptotic bounds of the statistical risk, allowing one to choose adaptively between rich and structured families of models and corresponding estimators. Two mathematical objects pervade the book: entropy and Gibbs measures. The goal is to show how to turn them into versatile and efficient technical tools, that will stimulate further studies and results.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 292 pp. Englisch.