Reproducing kernel Hilbert spaces associated with analytic translation-invariant Mercer kernels

DOI10.1007/s00041-007-9003-zzbMath1153.46017OpenAlexW1996956247MaRDI QIDQ939089

Ding-Xuan Zhou, Hongwei Sun

Publication date: 21 August 2008

Published in: The Journal of Fourier Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00041-007-9003-z

zbMATH Keywords

learning theorycovering numberreal analyticityreproducing kernel Hilbert spacederivative reproducingtranslation-invariant Mercer kernel

Mathematics Subject Classification ID

General nonlinear regression (62J02) Learning and adaptive systems in artificial intelligence (68T05) Hilbert spaces with reproducing kernels (= (proper) functional Hilbert spaces, including de Branges-Rovnyak and other structured spaces) (46E22)

Related Items (11)

Reproducing properties of differentiable Mercer-like kernels ⋮ Application of integral operator for regularized least-square regression ⋮ Gaussian process hydrodynamics ⋮ Reproducing Properties of Differentiable Mercer-Like Kernels on the Sphere ⋮ Covering numbers of Gaussian reproducing kernel Hilbert spaces ⋮ Differentiability of bizonal positive definite kernels on complex spheres ⋮ Some properties of Gaussian reproducing kernel Hilbert spaces and their implications for function approximation and learning theory ⋮ Applications of Bernstein-Durrmeyer operators in estimating the covering number ⋮ Old and New on the Laplace-Beltrami Derivative ⋮ The learning rates of regularized regression based on reproducing kernel Banach spaces ⋮ VECTOR VALUED REPRODUCING KERNEL HILBERT SPACES AND UNIVERSALITY

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