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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems - Vladimir Koltchinskii
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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… Altro …

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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems - nuovo libro

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… Altro …

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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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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) - edizione con copertina flessibile

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… Altro …

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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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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) - edizione con copertina flessibile

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… Altro …

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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 - nuovo libro

2011, ISBN: 3642221467

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

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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)

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.

Informazioni dettagliate del libro - 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
Copertina rigida
Copertina flessibile
Anno di pubblicazione: 2011
Editore: Springer
254 Pagine
Peso: 0,399 kg
Lingua: Englisch

Libro nella banca dati dal 2007-04-25T11:35:53+02:00 (Zurich)
Pagina di dettaglio ultima modifica in 2024-01-11T08:27:31+01:00 (Zurich)
ISBN/EAN: 9783642221460

ISBN - Stili di scrittura alternativi:
3-642-22146-7, 978-3-642-22146-0
Stili di scrittura alternativi e concetti di ricerca simili:
Autore del libro : erl vladimir, rademacher, norm
Titolo del libro: oracle, ecole ete probabilites saint flour, minim, probabilités, 2033, recovery, lecture notes mathematics, inequalities


Dati dell'editore

Autore: Vladimir Koltchinskii
Titolo: 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
Editore: Springer; Springer Berlin
254 Pagine
Anno di pubblicazione: 2011-07-29
Berlin; Heidelberg; DE
Stampato / Fatto in
Lingua: Inglese
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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