Concentration Inequalities and Model Selection: Ecole D'Eté de Probabilités de Saint-Flour XXXIII - 2003 (Lecture Notes in Mathematics / École d'Été ... de Saint-Flour XXXIII - 2003: 1896 - Tapa blanda
Sinopsis
Concentration inequalities have been recognized as fundamental tools in several domains such as geometry of Banach spaces or random combinatorics. They also turn to be essential tools to develop a non asymptotic theory in statistics. This volume provides an overview of a non asymptotic theory for model selection. It also discusses some selected applications to variable selection, change points detection and statistical learning.
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Acerca del autor
Prof. Massart has received the bronze medal of the CNRS (in mathematics and theoretical physics) in 1988 and the COPPS Presidents’ award in 1998.
De la contraportada
Since the impressive works of Talagrand, concentration inequalities have been recognized as fundamental tools in several domains such as geometry of Banach spaces or random combinatorics. They also turn out to be essential tools to develop a non-asymptotic theory in statistics, exactly as the central limit theorem and large deviations are known to play a central part in the asymptotic theory. An overview of a non-asymptotic theory for model selection is given here and some selected applications to variable selection, change points detection and statistical learning are discussed. This volume reflects the content of the course given by P. Massart in St. Flour in 2003. It is mostly self-contained and accessible to graduate students.
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Concentration Inequalities and Model Selection
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Since the impressive works of Talagrand, concentration inequalities have been recognized as fundamental tools in several domains such as geometry of Banach spaces or random combinatorics. They also turn out to be essential tools to develop a non-asymptotic theory in statistics, exactly as the central limit theorem and large deviations are known to play a central part in the asymptotic theory. An overview of a non-asymptotic theory for model selection is given here and some selected applications to variable selection, change points detection and statistical learning are discussed. This volume reflects the content of the course given by P. Massart in St. Flour in 2003. It is mostly self-contained andaccessible to graduate students. 360 pp. Englisch. Nº de ref. del artículo: 9783540484974
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Concentration Inequalities and Model Selection: Ecole d'Eté de Probabilités de Saint-Flour XXXIII - 2003 (Lecture Notes in Mathematics, 1896)
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CONCENTRATION INEQUALITIES AND MODEL SELECTION (PB 2007)
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Concentration Inequalities and Model Selection
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ISBN 10: 3540484973
ISBN 13: 9783540484974
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Taschenbuch. Condición: Neu. Neuware -Since the impressive works of Talagrand, concentration inequalities have been recognized as fundamental tools in several domains such as geometry of Banach spaces or random combinatorics. They also turn out to be essential tools to develop a non-asymptotic theory in statistics, exactly as the central limit theorem and large deviations are known to play a central part in the asymptotic theory. An overview of a non-asymptotic theory for model selection is given here and some selected applications to variable selection, change points detection and statistical learning are discussed. This volume reflects the content of the course given by P. Massart in St. Flour in 2003. It is mostly self-contained and accessible to graduate students.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 360 pp. Englisch. Nº de ref. del artículo: 9783540484974
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Concentration Inequalities and Model Selection : Ecole d'Eté de Probabilités de Saint-Flour XXXIII - 2003
Publicado por
Springer Berlin Heidelberg, 2007
ISBN 10: 3540484973
ISBN 13: 9783540484974
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Since the impressive works of Talagrand, concentration inequalities have been recognized as fundamental tools in several domains such as geometry of Banach spaces or random combinatorics. They also turn out to be essential tools to develop a non-asymptotic theory in statistics, exactly as the central limit theorem and large deviations are known to play a central part in the asymptotic theory. An overview of a non-asymptotic theory for model selection is given here and some selected applications to variable selection, change points detection and statistical learning are discussed. This volume reflects the content of the course given by P. Massart in St. Flour in 2003. It is mostly self-contained andaccessible to graduate students. Nº de ref. del artículo: 9783540484974
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