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Statistical learning theory and stochastic optimization : Ecole d'Eté de Probabilités de Saint-Flour XXXI-2001 Titelvorschau
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Statistical learning theory and stochastic optimization : Ecole d'Eté de Probabilités de Saint-Flour XXXI-2001

Verfasser/in: Olivier Catoni; Jean Picard; LINK (Online service)
Verlag: Berlin : Springer-Verlag, ©2004.
Serien: Lecture notes in mathematics (Springer-Verlag), 1851.
Ausgabe/Format   E-Book : Dokument : Tagungsband : EnglischAlle Ausgaben und Formate anzeigen
Datenbank:WorldCat
Zusammenfassung:
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  Weiterlesen…
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Gattung/Form: Electronic books
Conference papers and proceedings
Congresses
Physisches Format Print version:
Catoni, Olivier.
Statistical learning theory and stochastic optimization.
Berlin : Springer-Verlag, ©2004
(DLC) 2004109143
(OCoLC)56714791
Medientyp: Tagungsband, Dokument, Internetquelle
Dokumenttyp: Internet-Ressource, Computer-Datei
Alle Autoren: Olivier Catoni; Jean Picard; LINK (Online service)
ISBN: 9783540445074 3540445072
OCLC-Nummer: 56508135
Anmerkungen: " ... 31st Probability Summer School in Saint-Flour (July 8-25, 2001) ..."--Preface.
Beschreibung: 1 online resource (viii, 272 pages) : illustrations.
Inhalt: Universal Lossless Data Compression --
Links Between Data Compression and Statistical Estimation --
Non Cumulated Mean Risk --
Gibbs Estimators --
Randomized Estimators and Empirical Complexity --
Deviation Inequalities --
Markov Chains with Exponential Transitions --
References --
Index.
Serientitel: Lecture notes in mathematics (Springer-Verlag), 1851.
Andere Titel Ecole d'Eté de Probabilités de Saint-Flour XXXI-2001
Verfasserangabe: Olivier Catoni ; editor, Jean Picard.

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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  Weiterlesen…

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