Multiple Operator-valued Kernel Learning

Details Multiple Operator-valued Kernel Learning Multiple Operator-valued Kernel Learning

2012-03-07

arxiv.org/abs/1203.1596v1

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Machine Learning

No. RR-7900 (2012)

Scientific paper

This paper addresses the problem of learning a finite linear combination of operator-valued kernels. We study this problem in the case of kernel ridge regression for functional responses with a lr-norm constraint on the combination coefficients. We propose a multiple operator-valued kernel learning algorithm based on solving a system of linear operator equations by using a block coordinate descent procedure. We experimentally validate our approach on a functional regression task in the context of finger movement prediction in Brain-Computer Interface (BCI).

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