Nonlinear functional regression: a functional RKHS approach

This paper deals with functional regression, in which the input attributes as well as the response are functions. To deal with this problem, we develop a functional reproducing kernel Hilbert space approach; here, a kernel is an operator acting on a function and yielding a function. We demonstrate basic properties of these functional RKHS, as well as a representer theorem for this setting; we investigate the construction of kernels; we provide some experimental insight.

• Type: Journal
• Year: 2010
• Where: JMLR
• Authors: Hachem Kadri, Emmanuel Duflos, Philippe Preux, Stéphane Canu, Manuel Davy
• Keywords: Functional Regression, Functional Rkhs, JMLR 2010, Reproducing Kernel Hilbert Space