mloss.org IPCAhttp://mloss.orgUpdates and additions to IPCAenMon, 07 Jul 2014 10:25:03 -0000IPCA v0.1http://mloss.org/software/view/555/<html><p>Ideal PCA replaces the square kernel matrix k(X,X) in kernel PCA with a non-square kernel matrix k(X,Z) - the cross-kernel matrix - where Z are points different from the data input.
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<p>(a) Cross-kernels scale more favourably in the number of data points, allowing to obtain PCA-like components more quickly (in linear time).
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<p>(b) The right singular values of a cross-kernel-like matrix can be used for manifold learning with kernels.
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<p>The IPCA package allows extraction of both kind of features (left/right) and also implements several derived ones which can then be used in further learning tasks. See
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<p>Franz J. Király, Martin Kreuzer, Louis Theran. Learning with Cross-Kernels and IPCA.
http://arxiv.org/abs/1406.2646
</p></html>Franz Kiraly, Martin Kreuzer, Louis TheranMon, 07 Jul 2014 10:25:03 -0000http://mloss.org/software/rss/comments/555http://mloss.org/software/view/555/manifold learningfeature extractiondimension reductionprincipal components