Konferenzschrift | Kongress
Statistical learning theory and stochastic optimization
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. TOC: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.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISBN
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9783540225720
3540225722
- Dimensions
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24 cm
- Extent
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VIII, 272 S.
- Language
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Englisch
- Notes
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graph. Darst.
Literaturangaben
- Bibliographic citation
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Lecture notes in mathematics ; Vol. 1851
- Classification
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Mathematik
- Keyword
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Mathematische Lerntheorie
Stochastische Optimierung
- Event
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Veröffentlichung
- (where)
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Berlin, Heidelberg, New York
- (who)
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Springer
- (when)
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2004
- Contributor
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Catoni, Olivier
Picard, Jean
Ecole d'Eté de Probabilités (31 : 2001 : Saint-Flour)
- Table of contents
- Rights
-
Bei diesem Objekt liegt nur das Inhaltsverzeichnis digital vor. Der Zugriff darauf ist unbeschränkt möglich.
- Last update
-
11.06.2025, 2:15 PM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Object type
- Konferenzschrift
- Kongress
Associated
- Catoni, Olivier
- Picard, Jean
- Ecole d'Eté de Probabilités (31 : 2001 : Saint-Flour)
- Springer
Time of origin
- 2004
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Stochastic optimization methods
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