Kernel Hebbian algorithm for iterative kernel principal component analysis

Kim, Kwang In and Franz, Matthias O. and Schölkopf, Bernhard (2003) Kernel Hebbian algorithm for iterative kernel principal component analysis. Working Paper. Max Planck Institute for Biological Cybernetics.

[img]
Preview
PDF (\\lancs\homes\60\zhangy3\My Desktop\PURE PDF\Kernel)
Kernel.pdf - Submitted Version

Download (802kB)

Abstract

A new method for performing a kernel principal component analysis is proposed. By kernelizing the generalized Hebbian algorithm, one can iteratively estimate the principal components in a reproducing kernel Hilbert space with only linear order memory complexity. The derivation of the method and preliminary applications in image hyperresolution are presented. In addition, we discuss the extension of the method to the online learning of kernel principal components.

Item Type:
Monograph (Working Paper)
ID Code:
69829
Deposited By:
Deposited On:
03 Jul 2014 09:08
Refereed?:
No
Published?:
Published
Last Modified:
26 Sep 2020 00:18