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Regularization in kernel learning (Q847647)

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Language	Label	Description	Also known as
English	Regularization in kernel learning	scientific article

Statements

scholarly article

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Regularization in kernel learning (English)

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Shahar Mendelson

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The Annals of Statistics

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publication date

19 February 2010

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full work available at URL

https://arxiv.org/abs/1001.2094

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zbMATH Keywords

regression

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reproducing kernel Hilbert space

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regulation

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least-squares

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model selection

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MaRDI profile type

MaRDI publication profile

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FAST RATES FOR ESTIMATION ERROR AND ORACLE INEQUALITIES FOR MODEL SELECTION

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Local Rademacher complexities

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Empirical minimization

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\(\ell _{1}\)-regularized linear regression: persistence and oracle inequalities

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Statistical performance of support vector machines

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ESTIMATES OF SINGULAR NUMBERS OF INTEGRAL OPERATORS

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Optimal rates for the regularized least-squares algorithm

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On the mathematical foundations of learning

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Best choices for regularization parameters in learning theory: on the bias-variance problem.

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Learning Theory

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Uniform Central Limit Theorems

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Some limit theorems for empirical processes (with discussion)

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Subspaces and orthogonal decompositions generated by bounded orthogonal systems

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\(L_{p}\)-moments of random vectors via majorizing measures

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Local Rademacher complexities and oracle inequalities in risk minimization. (2004 IMS Medallion Lecture). (With discussions and rejoinder)

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The importance of convexity in learning with squared loss

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About the constants in Talagrand's concentration inequalities for empirical processes.

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Concentration inequalities and model selection. Ecole d'Eté de Probabilités de Saint-Flour XXXIII -- 2003.

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10.1162/1532443041424337

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Reconstruction and subgaussian operators in asymptotic geometric analysis

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Obtaining fast error rates in nonconvex situations

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On weakly bounded empirical processes

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Random vectors in the isotropic position

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Fast rates for support vector machines using Gaussian kernels

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ESTIMATING THE APPROXIMATION ERROR IN LEARNING THEORY

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Learning theory estimates via integral operators and their approximations

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Regularity of Gaussian processes

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Sharper bounds for Gaussian and empirical processes

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The Generic Chaining

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Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators

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Learning rates of least-square regularized regression

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The covering number in learning theory

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Identifiers

zbMATH Open document ID

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10.1214/09-AOS728

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:847647

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