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[PDF] Top 20 A Brief Digest on Reproducing Kernel Hilbert Space

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A Brief Digest on Reproducing Kernel Hilbert Space

A Brief Digest on Reproducing Kernel Hilbert Space

... Reproducing Kernel Hilbert Spaces (RKHS) have recently received much attention [1, 2, 3] from the statistics and machine learning researchers, due to the popularity of some machine learning ... See full document

5

Solving singular second-orderinitial/boundary value problems in reproducing kernel Hilbert space

Solving singular second-orderinitial/boundary value problems in reproducing kernel Hilbert space

... In this paper, we presents a reproducing kernel method for computing singular second-order initial/boundary value problems (IBVPs). This method could deal with much more general IBVPs than the ones could ... See full document

11

Generalisations of Pick's theorem to reproducing Kernel Hilbert spaces

Generalisations of Pick's theorem to reproducing Kernel Hilbert spaces

... The sufficient conditions derived in chapter 1 frustrated me. Numerous computer calculations with randomly chosen kernels that failed to satisfy the condition all found that the generalised Pick’s theorem also failed to ... See full document

120

Iterative sparse interpolation in reproducing kernel Hilbert spaces

Iterative sparse interpolation in reproducing kernel Hilbert spaces

... The publisher or other rights-holder may allow further reproduction and re-use of this version - refer to the White Rose Research Online record for this item.. Where records identify the[r] ... See full document

16

Learning Kernels for Semantic Clustering: A Deep Approach

Learning Kernels for Semantic Clustering: A Deep Approach

... Vector Space Models (VSMs), we propose to learn reproducing kernels in clas- sification ...in Hilbert spaces, ...learned kernel could be easily transferred to clustering methods, where the ... See full document

9

Solving multi-order fractional differential equations by reproducing kernel Hilbert space method

Solving multi-order fractional differential equations by reproducing kernel Hilbert space method

... Abstract In this paper, we propose a relatively new semi-analytical technique to approximate the solution of nonlinear multi-order fractional differential equations (FDEs). We present some results concerning to the ... See full document

21

Refinable Kernels

Refinable Kernels

... wavelet-like reproducing kernels. We also investigate a refinable kernel that forms a Riesz ...of reproducing kernel Hilbert ... See full document

38

Solving an inverse problem for a parabolic equation with a nonlocal boundary condition in the reproducing kernel space

Solving an inverse problem for a parabolic equation with a nonlocal boundary condition in the reproducing kernel space

... The rest of the paper is organized as follows. In section 2 we describe the governing equation. Several reproducing kernel spaces are defined in Section 3. The method implementation and convergence analysis ... See full document

20

Reconstruction of Sensory Stimuli Encoded with Integrate-and-Fire Neurons with Random Thresholds

Reconstruction of Sensory Stimuli Encoded with Integrate-and-Fire Neurons with Random Thresholds

... We present a general approach to the reconstruction of sensory stimuli encoded with leaky integrate-and-fire neurons with random thresholds. The stimuli are modeled as elements of a Reproducing Kernel ... See full document

14

Approximate solutions for MHD squeezing fluid flow by a novel method

Approximate solutions for MHD squeezing fluid flow by a novel method

... The reproducing kernel Hilbert space method (RKHSM) has been implemented to obtain a solution of the reduced fourth-order nonlinear boundary value ... See full document

17

Application of reproducing kernel Hilbert space method for solving second order fuzzy Volterra integro differential equations

Application of reproducing kernel Hilbert space method for solving second order fuzzy Volterra integro differential equations

... We have introduced a new method for solving second-order FVIDEs based on reproduc- ing kernel theory. The proposed technique gives solutions with good generalization and high exactness. The robustness of this ... See full document

15

Genomic-Assisted Prediction of Genetic Value With Semiparametric Procedures

Genomic-Assisted Prediction of Genetic Value With Semiparametric Procedures

... attractive. Kernel regression and reproducing kernel Hilbert spaces regression procedures are embedded into standard mixed-effects linear models, retaining additive genetic effects under ... See full document

16

Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces

Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces

... use reproducing kernel Hilbert spaces to provide characterizations of general notions of independence, and we use these characterizations to design objective functions to be ...use reproducing ... See full document

27

Study of Informative Value of Features in Rail Condition Monitoring

Study of Informative Value of Features in Rail Condition Monitoring

... to reproducing kernel Hilbert spaces ...ITL, kernel machines, and spectral machine learning techniques was ...approach kernel machines from a density estimation perspective, thus ... See full document

10

Gradient descent approach to approximation in reproducing kernel Hilbert spaces

Gradient descent approach to approximation in reproducing kernel Hilbert spaces

... The publisher or other rights-holder may allow further reproduction and re-use of this version - refer to the White Rose Research Online record for this item.. Where records identify the[r] ... See full document

21

Numerical solution of Troesch's problem using Christov rational functions

Numerical solution of Troesch's problem using Christov rational functions

... There are different techniques for solving Troesch’s problem. Temimi [25] proposed a new discontinuous Galerkin finite element method to solve this problem. Chang in [6] used the simple shooting method and in [5] the ... See full document

11

RECKONING OF PRISTINE SIGNAL AND MELIORATING ALGORITHM CONSTANCY BY OVERCOMING AMBIGUITY

RECKONING OF PRISTINE SIGNAL AND MELIORATING ALGORITHM CONSTANCY BY OVERCOMING AMBIGUITY

... Using Reproducing Kernel Hilbert Space based Independent Component Analysis (ICA) statistically independent vectors are ...with Reproducing Kernel Hilbert Space ... See full document

7

Some lemmas on reproducing kernel Hilbert spaces

Some lemmas on reproducing kernel Hilbert spaces

... The publisher or other rights-holder may allow further reproduction and re-use of this version - refer to the White Rose Research Online record for this item.. Where records identify the[r] ... See full document

12

New Implementation of Reproducing Kernel Method for Solving Functional Differential Equations

New Implementation of Reproducing Kernel Method for Solving Functional Differential Equations

... 2009 Solving Singular Second Order Three-Point Boundary Value Problems Using Reproducing Kernel Hilbert Space Method.. 2012 A Numerical Solution to Nonlinear Second Order Three-Point Bou[r] ... See full document

8

Model-free Variable Selection in Reproducing Kernel Hilbert Space

Model-free Variable Selection in Reproducing Kernel Hilbert Space

... Variable selection is popular in high-dimensional data analysis to identify the truly informa- tive variables. Many variable selection methods have been developed under various model assumptions. Whereas success has been ... See full document

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