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INFORMATIVE ENERGY METRIC FOR SIMILARITY MEASURE IN REPRODUCING KERNEL HILBERT SPACES [PDF]
International Journal of Computational Intelligence Systems, 2012 In this paper, information energy metric (IEM) is obtained by similarity computing for high-dimensional samples in a reproducing kernel Hilbert space (RKHS).
Songhua Liu, Junying Zhang, Caiying Ding
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Relative reproducing kernel Hilbert spaces [PDF]
, 2014 We introduce a reproducing kernel structure for Hilbert spaces of functions where differences of point evaluations are bounded.
Alpay, Daniel +2 more
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Mathematical Modelling and Analysis, 2018 Based on the reproducing kernel Hilbert space method, a new approach is proposed to approximate the solution of the Black-Scholes equation with Dirichlet boundary conditions and introduce the reproducing kernel properties in which the initial conditions ...
Mohammadreza Foroutan +2 more
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Reproducing Kernels and Variable Bandwidth
Journal of Function Spaces and Applications, 2012 We show that a modulation space of type () is a reproducing kernel Hilbert space (RKHS). In particular, we explore the special cases of variable bandwidth spaces Aceska and Feichtinger (2011) with a suitably chosen weight to provide strong enough decay ...
R. Aceska, H. G. Feichtinger
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On Weights Which Admit Harmonic Bergman Kernel and Minimal Solutions of Laplace’s Equation
Annales Mathematicae Silesianae, 2022 In this paper we consider spaces of weight square-integrable and harmonic functions L2H(Ω, µ). Weights µ for which there exists reproducing kernel of L2H(Ω, µ) are named ’admissible weights’ and such kernels are named ’harmonic Bergman kernels’. We prove
Żynda Tomasz Łukasz
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Alexandria Engineering Journal, 2021 This paper proposes an advanced numerical-analytical approach for handling a class of fuzzy fractional differential equations involving Caputo-Fabrizio derivative with a non-singular kernel arsing in the medical sector. The solution methodology relies on
Nesrine Harrouche +3 more
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Probability Error Bounds for Approximation of Functions in Reproducing Kernel Hilbert Spaces
Journal of Function Spaces, 2021 We find probability error bounds for approximations of functions f in a separable reproducing kernel Hilbert space H with reproducing kernel K on a base space X, firstly in terms of finite linear combinations of functions of type Kxi and then in terms of
Ata Deniz Aydın, Aurelian Gheondea
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Semi reproducing kernel hilbert spaces and mixed precision computation. [PDF]
, 2018 Positive definite and conditionally positive definite functions are widely used in interpolation and smoothing problems, particularly when the data is scattered.
Garing, Ronald
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Approximation Analysis of Learning Algorithms for Support Vector Regression and Quantile Regression
Journal of Applied Mathematics, 2012 We study learning algorithms generated by regularization schemes in reproducing kernel Hilbert spaces associated with an ϵ-insensitive pinball loss. This loss function is motivated by the ϵ-insensitive loss for support vector regression and the pinball ...
Dao-Hong Xiang, Ting Hu, Ding-Xuan Zhou
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Reproducing kernel Hilbert spaces of Gaussian priors
, 2008 We review definitions and properties of reproducing kernel Hilbert spaces attached to Gaussian variables and processes, with a view to applications in nonparametric Bayesian statistics using Gaussian priors.
Vaart, AW Aad van der +7 more
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