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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 ... / École d'Été de Probabilités de Saint-Flour) - Vladimir Koltchinskii
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Vladimir Koltchinskii:
Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d'Été de Probabilités de Saint-Flour XXXVIII-2008 (Lecture ... / École d'Été de Probabilités de Saint-Flour) - Livres de poche

2008, ISBN: 3642221467

[SR: 1426778], Paperback, [EAN: 9783642221460], Springer, Springer, Book, [PU: Springer], Springer, 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., 13983, Probability & Statistics, 226699, Applied, 13884, Mathematics, 75, Science & Math, 1000, Subjects, 283155, Books, 491548, Statistics, 468218, Mathematics, 468216, Science & Mathematics, 465600, New, Used & Rental Textbooks, 2349030011, Specialty Boutique, 283155, Books

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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) - Vladimir Koltchinskii
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Vladimir Koltchinskii:
Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d’Été de Probabilités de Saint-Flour XXXVIII-2008 (Lecture Notes in Mathematics) - Livres de poche

2008, ISBN: 3642221467

[SR: 2440230], Paperback, [EAN: 9783642221460], Springer, Springer, Book, [PU: Springer], Springer, 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., 13983, Probability & Statistics, 226699, Applied, 13884, Mathematics, 75, Science & Math, 1000, Subjects, 283155, Books, 491548, Statistics, 468218, Mathematics, 468216, Science & Mathematics, 465600, New, Used & Rental Textbooks, 2349030011, Specialty Boutique, 283155, Books

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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d'Été de - Vladimir Koltchinskii
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d'Été de - nouveau livre

ISBN: 9783642221460

ID: 978364222146

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. Vladimir Koltchinskii, Books, Science and Nature, Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d'Été de Books>Science and Nature, Springer Berlin Heidelberg

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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems - Koltchinskii, Vladimir
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Koltchinskii, Vladimir:
Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems - Livres de poche

2011, ISBN: 9783642221460

[ED: Softcover], [PU: Springer, Berlin], 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. 2011. 2011. ix, 254 S. IX, 254p. 235 mm Versandfertig in 3-5 Tagen, DE, Neuware, gewerbliches Angebot, offene Rechnung (Vorkasse vorbehalten)

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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d'Été de Probabilités de Saint-Flour XXXVIII-2008 - Vladimir Koltchinskii
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Vladimir Koltchinskii:
Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d'Été de Probabilités de Saint-Flour XXXVIII-2008 - Livres de poche

2008, ISBN: 9783642221460

ID: 9783642221460

Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d'Été de Probabilités de Saint-Flour XXXVIII-2008 Oracle-Inequalities-in-Empirical-Risk-Minimization-and-Sparse-Recovery-Problems~~Vladimir-Koltchinskii Science/Tech>Statistics & Probability>Statistics & Probability Paperback, Springer Berlin Heidelberg

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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems

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.

Informations détaillées sur le livre - Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems


EAN (ISBN-13): 9783642221460
ISBN (ISBN-10): 3642221467
Version reliée
Livre de poche
Date de parution: 2011
Editeur: Springer-Verlag GmbH
254 Pages
Poids: 0,399 kg
Langue: Englisch

Livre dans la base de données depuis 25.04.2007 11:35:53
Livre trouvé récemment le 02.07.2017 13:18:28
ISBN/EAN: 9783642221460

ISBN - Autres types d'écriture:
3-642-22146-7, 978-3-642-22146-0


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