Softwares
The following are Matlab codes for some algorithms.
Gradient-based kernel dimension reduction
gKDR_matlab.zip
Reference: K. Fukumizu and C.Leng (2013) Gradient-based kernel dimension reduction for
regression.
Journal of the American Statistical Association, to appear. paper
Comment: This algorithm gKDR is much faster than KDR (below). It does not need numerical optimization but only eigendecomposition, and thus covers high-dimensional data. The previous KDR (kernel dimension reduction) needs non-convex optimization, but provides very accurate results for small data sets.
Kernel dimension reduction for regression
KDR_open_new.zip
References:
Fukumizu, K. Francis R. Bach and M. Jordan.
Kernel dimension reduction in regression.
The Annals of Statistics. 37(4), pp.1871-1905 (2009)
pdf file
Fukumizu, K., Bach, F.R., and Jordan, M.I. "Dimensionality reduction for
supervised learning with reproducing kernel Hilbert spaces",
Journal of Machine Learning Research. 5(Jan):73-99, 2004.
pdf
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