Nonlinear functional regression: a functional RKHS approach

@inproceedings{Kadri2010NonlinearFR,
  title={Nonlinear functional regression: a functional RKHS approach},
  author={Hachem Kadri and Emmanuel Duflos and Philippe Preux and St{\'e}phane Canu and Manuel Davy},
  booktitle={AISTATS},
  year={2010}
}
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. 
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