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Differentiability of bizonal positive definite kernels on complex spheres
(Academic PressElsevierSan Diego, 2014-04-01)
We prove that any continuous function with domain {z ∈ C: |z| ≤ 1} that generates a bizonal positive definite kernel on the unit sphere in 'C POT.Q' , q ⩾ 3, is continuously differentiable in {z ∈ C: |z| < 1} up to order ...
Reproducing kernel Hilbert spaces associated with kernels on topological spaces
(CONSULTANTS BUREAU/SPRINGERNEW YORK, 2012)
We analyze reproducing kernel Hilbert spaces of positive definite kernels on a topological space X being either first countable or locally compact. The results include versions of Mercer's theorem and theorems on the ...
REPRESENTATION OF MEASURABLE POSITIVE DEFINITE GENERALIZED TOEPLITZ KERNELS IN R
(Integral equations and operator theory., 2013)
Weighted Fourier–Laplace transforms in reproducing kernel Hilbert spaces on the sphere
(Academic PressElsevierSan Diego, 2014-03-15)
We study the action of a weighted Fourier–Laplace transform on the functions in the reproducing kernel Hilbert space (RKHS) associated with a positive definite kernel on the sphere. After defining a notion of smoothness ...
Spectral mixture kernels for Multi-Output Gaussian processes
(Universidad de Chile, 2017)
Multi-Output Gaussian Processes (MOGPs) are the multivariate extension of Gaussian processes (GPs \cite{Rasmussen:2006}), a Bayesian nonparametric method for univariate regression. MOGPs address the multi-channel regression ...
WRONSKIANS OF FOURIER AND LAPLACE TRANSFORMS
(Amer Mathematical Soc, 2019-09-15)
Associated with a given suitable function, or a measure, on R, we introduce a correlation function so that the Wronskian of the Fourier transform of the function is the Fourier transform of the corresponding correlation ...
Relevant data representation by a Kernel-based framework
(2015)
Nowadays, the analysis of a large amount of data has emerged as an issue of great interest taking increasing place in the scientific community, especially in automation, signal processing, pattern recognition, and machine ...
Relevant multichannel time series representation based on functional measures in RKHS
(Manizales - Ingeniería y Arquitectura - Doctorado en Ingeniería - AutomáticaDepartamento de Ingeniería Eléctrica y ElectrónicaUniversidad Nacional de Colombia - Sede Manizales, 2020)
Kernels methods provide a powerful and unifying framework to solve nonlinear problems while retaining in many cases, the simplicity of linear solutions. However, in machine learning and kernels methods, data is assumed to ...