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A Fast Algorithm for Updating and Downsizing the Dominant Kernel Principal Components

โœ Scribed by Mastronardi, Nicola; Tyrtyshnikov, Eugene E.; Van Dooren, Paul


Book ID
111692617
Publisher
Society for Industrial and Applied Mathematics
Year
2010
Tongue
English
Weight
548 KB
Volume
31
Category
Article
ISSN
0895-4798

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The dominant set of eigenvectors of the symmetrical kernel Gram matrix is used in many important kernel methods (like e.g. kernel Principal Component Analysis, feature approximation, denoising, compression, prediction) in the machine learning area. Yet in the case of dynamic and/or large-scale data,