Logo eprints

Approximation and Estimation Bounds for Subsets of Reproducing Kernel Kreǐn Spaces

Gnecco, Giorgio Approximation and Estimation Bounds for Subsets of Reproducing Kernel Kreǐn Spaces. Neural Processing Letters, 39 (2). pp. 137-153. ISSN 1370-4621 (2014)

This is the latest version of this item.

Full text not available from this repository.

Abstract

Reproducing kernel Kreın spaces are used in learning from data via kernel methods when the kernel is indefinite. In this paper, a characterization of a subset of the unit ball in such spaces is provided. Conditions are given, under which upper bounds on the estimation error and the approximation error can be applied simultaneously to such a subset. Finally, it is shown that the hyperbolic-tangent kernel and other indefinite kernels satisfy such conditions.

Item Type: Article
Identification Number: 10.1007/s11063-013-9294-9
Uncontrolled Keywords: Reproducing Kernel Kreǐn Spaces; Estimation error; Approximation error; Rademacher complexity
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Research Area: Computer Science and Applications
Depositing User: Giorgio Gnecco
Date Deposited: 17 Sep 2013 07:43
Last Modified: 18 Feb 2015 11:35
URI: http://eprints.imtlucca.it/id/eprint/1748

Available Versions of this Item

Actions (login required)

Edit Item Edit Item