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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d’Été de Probabilités de Saint-Flour XXXVIII-2008 - Couverture souple
Synopsis
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.
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Présentation de l'éditeur
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.
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems : École d¿Été de Probabilités de Saint-Flour XXXVIII-2008
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Springer Berlin Heidelberg, 2011
ISBN 10 : 3642221467
ISBN 13 : 9783642221460
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d'Été de Probabilités de Saint-Flour XXXVIII-2008
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems
Edité par
Springer Berlin Heidelberg, 2011
ISBN 10 : 3642221467
ISBN 13 : 9783642221460
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a unified framework for machine learning problems (such as large margin classification), sparse recovery and low rank matrix problemsDevelops a variety of probabilistic inequalities for empirical processes needed to obtain error bounds in machine l. N° de réf. du vendeur 5052788
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: �cole d'�t� de Probabilit�s de Saint-Flour XXXVIII-2008 (Lecture Notes in Mathematics)
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems : École d¿Été de Probabilités de Saint-Flour XXXVIII-2008
Edité par
Springer Berlin Heidelberg, 2011
ISBN 10 : 3642221467
ISBN 13 : 9783642221460
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9783642221460
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems
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Springer Berlin Heidelberg Jul 2011, 2011
ISBN 10 : 3642221467
ISBN 13 : 9783642221460
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 268 pp. Englisch. N° de réf. du vendeur 9783642221460
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems : Ecole d'Ete de Probabilites de Saint-Flour XXXVIII-2008
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems : Ecole d'Ete de Probabilites de Saint-Flour XXXVIII-2008
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems
Edité par
Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 2011, 2011
ISBN 10 : 3642221467
ISBN 13 : 9783642221460
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 268 pp. Englisch. N° de réf. du vendeur 9783642221460
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems : Ecole d'Ete de Probabilites de Saint-Flour XXXVIII-2008
Edité par
Springer, 2011
ISBN 10 : 3642221467
ISBN 13 : 9783642221460
Ancien ou d'occasion
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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