Canonical Correlation Analysis based on Kernel Independence Measures
Canonical correlation analysis that extracts nonlinear correlation through the use of Hilbert Schmidt Independence Criterion and Centered Kernel Target Alignment.
Billy Chang: <firstname.lastname@example.org>
Chang et. al. (2013) Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment. ICML 2013.
Gretton et. al. (2005) Measuring statistical dependence with Hilbert-Schmidt Norm. In Algorithmic Learning Theory 2005.
Cortes et. al. (2012) Algorithms for learning kernels based on centered alignments. JMLR 13:795-828.
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