Fast iterative kernel principal component analysis
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Guenter, Simon; Schraudolph, Nicol; Vishwanathan, S
Description
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]
Collections | ANU Research Publications |
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Date published: | 2007-08 |
Type: | Journal article |
URI: | http://hdl.handle.net/10440/298 http://digitalcollections.anu.edu.au/handle/10440/298 |
Source: | Journal of Machine Learning Research |
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File | Description | Size | Format | Image |
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Guenter_Fast2007.pdf | 3.11 MB | Adobe PDF |
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