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Communication Dans Un Congrès Année : 2010

Nonlinear functional regression: a functional RKHS approach

Hachem Kadri
Emmanuel Duflos
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Manuel Davy
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Résumé

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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Dates et versions

hal-00510411 , version 1 (18-08-2010)

Identifiants

  • HAL Id : hal-00510411 , version 1

Citer

Hachem Kadri, Emmanuel Duflos, Philippe Preux, Stephane Canu, Manuel Davy. Nonlinear functional regression: a functional RKHS approach. Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS'10), 2010, Italy. pp.374-380. ⟨hal-00510411⟩
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