Results 61 to 70 of about 13,358 (271)
Mathematical Methods in the Applied Sciences, EarlyView.A highly accurate numerical method is given for the solution of boundary value problem of generalized Bagley‐Torvik (BgT) equation with Caputo derivative of order 0<β<2$$ 0<\beta <2 $$ by using the collocation‐shooting method (C‐SM). The collocation solution is constructed in the space Sm+1(1)$$ {S}_{m+1}^{(1)} $$ as piecewise polynomials of degree at ...
Suzan Cival Buranay +2 more
wiley +1 more source
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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AIMS Mathematics, 2021 In this paper, the reproducing kernel Hilbert space method had been extended to model a numerical solution with two-point temporal boundary conditions for the fractional derivative in the Caputo sense, convergent analysis and error bounds are discussed ...
Yassamine Chellouf +4 more
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Combining kernelised autoencoding and centroid prediction for dynamic multi‐objective optimisation
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Evolutionary algorithms face significant challenges when dealing with dynamic multi‐objective optimisation because Pareto optimal solutions and/or Pareto optimal fronts change. The authors propose a unified paradigm, which combines the kernelised autoncoding evolutionary search and the centroid‐based prediction (denoted by KAEP), for solving ...
Zhanglu Hou +4 more
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Abstract and Applied Analysis, 2014 A numerical method based on the reproducing kernel theorem is presented for the numerical solution of a three-point boundary value problem with an integral condition.
Jing Niu, Ping Li
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International Statistical Review, EarlyView.Summary Distance covariance is a popular measure of dependence between random variables. It has some robustness properties, but not all. We prove that the influence function of the usual distance covariance is bounded, but that its breakdown value is zero.
Sarah Leyder +2 more
wiley +1 more source
Reproducing Kernel Hilbert Space Choice Model [PDF]
Proceedings of the 26th ACM Conference on Economics and ComputationYiqi Yang, Zhi Wang, Rui Gao, Shuang Li
openalex +2 more sources
Journal of Time Series Analysis, EarlyView.ABSTRACT Expectile is a coherent and elicitable law‐invariant risk measure widely applied in risk management. Existing methods based on iteratively reweighted least squares (IWLS) are not computationally efficient for large‐scale sample sizes. To overcome the issue, we develop a direct nonparametric conditional expectile function estimator by inverting
Feipeng Zhang, Ping‐Shou Zhong
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Advances in Difference Equations, 2021 This paper deals with the generalized Bagley–Torvik equation based on the concept of the Caputo–Fabrizio fractional derivative using a modified reproducing kernel Hilbert space treatment.
Shatha Hasan +5 more
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A Reproducing Kernel Hilbert Space Approach to Functional Linear Regression [PDF]
, 2010 We study in this paper a smoothness regularization method for functional linear regression and provide a unified treatment for both the prediction and estimation problems.
M. Yuan, Tommaso Cai
semanticscholar +1 more source