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＜電子ブック＞
Concentration Inequalities and Model Selection : Ecole d'Eté de Probabilités de Saint-Flour XXXIII - 2003 / by Pascal Massart ; edited by Jean Picard
(École d'Été de Probabilités de Saint-Flour ; 1896)

版	1st ed. 2007.
出版者	(Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer)
出版年	2007
本文言語	英語
大きさ	XIV, 343 p : online resource
著者標目	*Massart, Pascal author Picard, Jean editor SpringerLink (Online service)
件　名	LCSH:Probabilities LCSH:Statistics  LCSH:Computer science -- Mathematics  全ての件名で検索 FREE:Probability Theory FREE:Statistical Theory and Methods FREE:Mathematical Applications in Computer Science
一般注記	Exponential and Information Inequalities -- Gaussian Processes -- Gaussian Model Selection -- Concentration Inequalities -- Maximal Inequalities -- Density Estimation via Model Selection -- Statistical Learning 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 HTTP:URL=https://doi.org/10.1007/978-3-540-48503-2

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