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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems - Vladimir Koltchinskii
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems - new book

2011, ISBN: 3642221467

The purpose of these lecture notes is to provide an introduction to the general theory of empirical risk minimization with an emphasis on excess risk bounds and oracle inequalities in pen… More...

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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems - new book

ISBN: 9783642221460

The purpose of these lecture notes is to provide an introduction to the general theory of empirical risk minimization with an emphasis on excess risk bounds and oracle inequalities in pen… More...

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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d?Été de Probabilités de Saint-Flour XXXVIII-2008 (Lecture Notes in Mathematics, Band 2033) - Koltchinskii, Vladimir
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Koltchinskii, Vladimir:
Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d?Été de Probabilités de Saint-Flour XXXVIII-2008 (Lecture Notes in Mathematics, Band 2033) - Paperback

2011

ISBN: 9783642221460

Springer, Taschenbuch, Auflage: 2011, 268 Seiten, Publiziert: 2011-07-29T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: biography, 0.84 kg, Verkaufsrang: 5029738, Statistik, Naturwissens… More...

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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d?Été de Probabilités de Saint-Flour XXXVIII-2008 (Lecture Notes in Mathematics, Band 2033) - Koltchinskii, Vladimir
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Koltchinskii, Vladimir:
Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d?Été de Probabilités de Saint-Flour XXXVIII-2008 (Lecture Notes in Mathematics, Band 2033) - Paperback

2011, ISBN: 9783642221460

Springer, Taschenbuch, Auflage: 2011, 268 Seiten, Publiziert: 2011-07-29T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: biography, 0.84 kg, Verkaufsrang: 5029738, Statistik, Naturwissens… More...

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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems École d¿Été de Probabilités de Saint-Flour XXXVIII-2008 - Koltchinskii, Vladimir
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems École d¿Été de Probabilités de Saint-Flour XXXVIII-2008 - new book

2011, ISBN: 3642221467

2011 Kartoniert / Broschiert Wahrscheinlichkeit - Wahrscheinlichkeitstheorie, Wahrscheinlichkeitsrechnung und Statistik, 62J99,62H12,60B20,60G99; concentrationinequalities; empiricalpro… More...

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Details of the book
Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d?Été de Probabilités de Saint-Flour XXXVIII-2008 (Lecture Notes in Mathematics, Band 2033)

The purpose of these lecture notes is to provide an introduction to the general theory of empirical risk minimization with an emphasis on excess risk bounds and oracle inequalities in penalized problems. In recent years, there have been new developments in this area motivated by the study of new classes of methods in machine learning such as large margin classification methods (boosting, kernel machines). The main probabilistic tools involved in the analysis of these problems are concentration and deviation inequalities by Talagrand along with other methods of empirical processes theory (symmetrization inequalities, contraction inequality for Rademacher sums, entropy and generic chaining bounds). Sparse recovery based on l_1-type penalization and low rank matrix recovery based on the nuclear norm penalization are other active areas of research, where the main problems can be stated in the framework of penalized empirical risk minimization, and concentration inequalities and empirical processes tools have proved to be very useful.

Details of the book - Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d?Été de Probabilités de Saint-Flour XXXVIII-2008 (Lecture Notes in Mathematics, Band 2033)


EAN (ISBN-13): 9783642221460
ISBN (ISBN-10): 3642221467
Hardcover
Paperback
Publishing year: 2011
Publisher: Springer
254 Pages
Weight: 0,399 kg
Language: Englisch

Book in our database since 2007-04-25T10:35:53+01:00 (London)
Detail page last modified on 2024-01-11T07:27:31+00:00 (London)
ISBN/EAN: 3642221467

ISBN - alternate spelling:
3-642-22146-7, 978-3-642-22146-0
Alternate spelling and related search-keywords:
Book author: erl vladimir, rademacher, norm
Book title: oracle, ecole ete probabilites saint flour, minim, probabilités, 2033, recovery, lecture notes mathematics, inequalities


Information from Publisher

Author: Vladimir Koltchinskii
Title: Lecture Notes in Mathematics; École d'Été de Probabilités de Saint-Flour; Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems - École d’Été de Probabilités de Saint-Flour XXXVIII-2008
Publisher: Springer; Springer Berlin
254 Pages
Publishing year: 2011-07-29
Berlin; Heidelberg; DE
Printed / Made in
Language: English
80,24 € (DE)
82,49 € (AT)
88,50 CHF (CH)
POD
IX, 254 p.

BC; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; Mathematik; 62J99, 62H12, 60B20, 60G99; concentration inequalities; empirical processes; low rank matrix recovery; sparse recovery; Probability Theory; Stochastik; EA

The purpose of these lecture notes is to provide an introduction to the general theory of empirical risk minimization with an emphasis on excess risk bounds and oracle inequalities in penalized problems. In recent years, there have been new developments in this area motivated by the study of new classes of methods in machine learning such as large margin classification methods (boosting, kernel machines). The main probabilistic tools involved in the analysis of these problems are concentration and deviation inequalities by Talagrand along with other methods of empirical processes theory (symmetrization inequalities, contraction inequality for Rademacher sums, entropy and generic chaining bounds). Sparse recovery based on l_1-type penalization and low rank matrix recovery based on the nuclear norm penalization are other active areas of research, where the main problems can be stated in the framework of penalized empirical risk minimization, and concentration inequalities and empirical processes tools have proved to be very useful.
Provides a unified framework for machine learning problems (such as large margin classification), sparse recovery and low rank matrix problems Develops a variety of probabilistic inequalities for empirical processes needed to obtain error bounds in machine learning and sparse recovery Develops a comprehensive theory of excess risk bounds and oracle inequalities for penalized empirical risk minimization Includes supplementary material: sn.pub/extras

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