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

Author: Olivier Catoni; Jean Picard
Publisher: Berlin ; New York : Springer, ©2004.
Series: Lecture notes in mathematics (Springer-Verlag), 1851.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:

Statistical learning theory is aimed at analyzing complex data with necessarily approximate models. The author focuses on non-asymptotic bounds of the statistical risk, allowing one to choose  Read more...

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Genre/Form: Kongress
Conference papers and proceedings
Congresses
Congrès
Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Olivier Catoni; Jean Picard
ISBN: 3540225722 9783540225720
OCLC Number: 56714791
Notes: "Lectures were given at the 31st Probability Summer School in Saint-Flour (July 8-25, 2001)"--Preface.
Description: viii, 272 pages : illustrations ; 24 cm.
Contents: 1. Universal lossless data compression --
2. Links between data compression and statistical estimation --
3. Non cumulated mean risk --
4. Gibbs estimators --
5. Randomized estimators and empirical complexity --
6. Deviation inequalities --
7. Markov chains with exponential transitions.
Series Title: Lecture notes in mathematics (Springer-Verlag), 1851.
Other Titles: Ecole d'Eté de Probabilités de Saint-Flour XXXI--2001
Responsibility: Olivier Catoni ; editor, Jean Picard.
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