Results 131 to 140 of about 11,485 (217)
The Schur algorithm and reproducing kernel Hilbert spaces in the ball
Daniel Alpay+2 more
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Soft and hard classification by reproducing kernel Hilbert space methods
Grace Wahba
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Subspace regression in reproducing kernel hilbert space
L. Hoegaerts+3 more
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Kernel Principal Component Regression in Reproducing Kernel Hilbert Space
Chooleewan Dachapak+3 more
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Optimal sampling points in reproducing kernel Hilbert spaces [PDF]
Rui Wang, Haizhang Zhang
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Some Lemmas on Reproducing Kernel Hilbert Spaces [PDF]
Reproducing kernel Hilbert spaces (RKHS) provides a framework for approximation from finite data using the idea of bounded linear functionals. The approximation problem in this case can be viewed as the inverse problem of finding the optimum operator from the Euclidean space of observations to some subspace of the RKHS.
Dodd, T.J., Harrison, R.F.
openaire
Single-Image Super-Resolution via an Iterative Reproducing Kernel Hilbert Space Method
Liang-Jian Deng+2 more
semanticscholar +1 more source
Nonlinear functional models for functional responses in reproducing kernel Hilbert spaces
Heng Lian
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