Kernel Dimension Reduction in Regression 1

@inproceedings{Fukumizu2009KernelDR,
  title={Kernel Dimension Reduction in Regression 1},
  author={Kenji Fukumizu and Francis R. Bach and Michael I. Jordan},
  year={2009}
}
We present a new methodology for sufficient dimension reduction (SDR). Our methodology derives directly from the formulation of SDR in terms of the conditional independence of the covariate X from the response Y , given the projection of X on the central subspace [cf. J. Amer. Statist. Assoc. 86 (1991) 316–342 and Regression Graphics (1998) Wiley]. We show that this conditional independence assertion can be characterized in terms of conditional covariance operators on reproducing kernel Hilbert… CONTINUE READING
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