Concentration Inequalities and Model Selection : Ecole d'Etï½ de Probabilitï½s de Saint-Flour XXXIII - 2003 - Pascal Massart

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Concentration Inequalities and Model Selection

Ecole d'Etï½ de Probabilitï½s de Saint-Flour XXXIII - 2003

By: Pascal Massart, Jean Picard (Editor)

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Paperback | 18 April 2007

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360 Pages

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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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You Can Find This Book In

Non-Fiction Mathematics Probability & Statistics Applied Mathematics Topology Combinatorics & Graph Theory Computing & I.T.Computer Science Mathematical Theory of Computation

Introduction	p. 1
Exponential and information inequalities	p. 15
Gaussian processes	p. 53
Gaussian model selection	p. 83
Concentration inequalities	p. 147
Maximal inequalities	p. 183
Density estimation via model selection	p. 201
Statistical learning	p. 279
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Concentration Inequalities and Model Selection

Ecole d'Etï½ de Probabilitï½s de Saint-Flour XXXIII - 2003

At a Glance

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