Error bounds for suboptimal solutions to kernel principal component analysis

Gnecco, Giorgio and Sanguineti, Marcello Error bounds for suboptimal solutions to kernel principal component analysis. Optimization Letters, 4 (2). pp. 197-210. ISSN 1862-4472 (2010)

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Abstract

Suboptimal solutions to kernel principal component analysis are considered. Such solutions take on the form of linear combinations of all n-tuples of kernel functions centered on the data, where n is a positive integer smaller than the cardinality m of the data sample. Their accuracy in approximating the optimal solution, obtained in general for n = m, is estimated. The analysis made in Gnecco and Sanguineti (Comput Optim Appl 42:265–287, 2009) is extended. The estimates derived therein for the approximation of the first principal axis are improved and extensions to the successive principal axes are derived.

Item Type:	Article
Identification Number:	https://doi.org/10.1007/s11590-009-0158-1
Uncontrolled Keywords:	Principal component analysis (PCA); Kernel methods; Suboptimal solutions
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Research Area:	Computer Science and Applications
Depositing User:	Giorgio Gnecco
Date Deposited:	13 Sep 2013 09:40
Last Modified:	16 Sep 2013 12:03
URI:	http://eprints.imtlucca.it/id/eprint/1710

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• Error bounds for suboptimal solutions to kernel principal component analysis. (deposited 13 Sep 2013 09:40) [Currently Displayed]
  • Error Bounds for Suboptimal Solutions to Kernel Principal Component Analysis. (deposited 17 Sep 2013 13:09)

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