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Fast iterative kernel principal component analysis

Guenter, Simon; Schraudolph, Nicol; Vishwanathan, S


We develop gain adaptation methods that improve convergence of the kernel Hebbian algorithm (KHA) for iterative kernel PCA (Kim et al., 2005). KHA has a scalar gain parameter which is either held constant or decreased according to a predetermined annealing schedule, leading to slow convergence. We accelerate it by incorporating the reciprocal of the current estimated eigenvalues as part of a gain vector. An additional normalization term then allows us to eliminate a tuning parameter in the...[Show more]

CollectionsANU Research Publications
Date published: 2007-08
Type: Journal article
Source: Journal of Machine Learning Research


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