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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 ...
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 ...
Branching problems in reproducing kernel spaces
(Duke University Press, 2020-12-01)
For a semisimple Lie group G satisfying the equal-rank condition, the most basic family of unitary irreducible representations is the discrete series found by Harish-Chandra. In our work here we study some of the branching ...
A converse sampling theorem in reproducing kernel Banach spaces
(Springer Nature, 2022)
Branching problems for semisimple Lie groups and reproducing kernelsRègles de branchement pour les groupes de Lie semi-simples et les noyaux reproduisants
(Elsevier France-editions Scientifiques Medicales Elsevier, 2019-09)
For a semisimple Lie group G satisfying the equal rank condition, the most basic family of unitary irreducible representations is the discrete series found by Harish-Chandra. In this paper, we study some of the branching ...
Grassmann geometry of zero sets in reproducing kernel Hilbert spaces
(Academic Press Inc Elsevier Science, 2021-08)
Let H be a reproducing kernel Hilbert space of functions on a set X. We study the problem of finding a minimal geodesic of the Grassmann manifold of H that joins two subspaces consisting of functions which vanish on given ...
Learning representations for classification problems in reproducing kernel Hilbert spaces
(Universidade Federal de Minas GeraisBrasilENG - DEPARTAMENTO DE ENGENHARIA ELÉTRICAPrograma de Pós-Graduação em Engenharia ElétricaUFMG, 2020-10-26)
O desempenho de um modelo de aprendizado de máquina, independentemente da tarefa, depende da qualidade das representações que o fornecemos. Há uma ampla classe de métodos que utilizam propriedades estatísticas de um conjunto ...
A Lagrangian reproducing kernel particle method for metal forming analysis
(Springer VerlagNew YorkEUA, 1998)