Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Mathematics (LNM, volume 1896)
Part of the book sub series: École d'Été de Probabilités de Saint-Flour (LNMECOLE)
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Table of contents (8 chapters)
Keywords
About this book
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.
Authors, Editors and Affiliations
About the editor
Bibliographic Information
Book Title: Concentration Inequalities and Model Selection
Book Subtitle: Ecole d'Eté de Probabilités de Saint-Flour XXXIII - 2003
Authors: Pascal Massart
Editors: Jean Picard
Series Title: Lecture Notes in Mathematics
DOI: https://doi.org/10.1007/978-3-540-48503-2
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2007
Softcover ISBN: 978-3-540-48497-4Published: 18 April 2007
eBook ISBN: 978-3-540-48503-2Published: 26 April 2007
Series ISSN: 0075-8434
Series E-ISSN: 1617-9692
Edition Number: 1
Number of Pages: XIV, 343
Topics: Probability Theory and Stochastic Processes, Statistical Theory and Methods, Information and Communication, Circuits