Massart / Picard Concentration Inequalities and Model Selection

Ecole d'Eté de Probabilités de Saint-Flour XXXIII - 2003
2007
ISBN: 978-3-540-48503-2
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 1896, 343 Seiten, eBook

Reihe: Lecture Notes in Mathematics

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.

Zielgruppe

Research

Autoren/Hrsg.

Massart, Pascal

Picard, Jean

Inhaltsverzeichnis

Exponential and Information Inequalities.- Gaussian Processes.- Gaussian Model Selection.- Concentration Inequalities.- Maximal Inequalities.- Density Estimation via Model Selection.- Statistical Learning.

Über Autor(innen)

Prof. Massart has received the bronze medal of the CNRS (in mathematics and theoretical physics) in 1988 and the COPPS Presidents’ award in 1998.