Results 1 to 10 of about 856,472 (265)
Oscillation in a posteriori error estimation [PDF]
Numerische Mathematik, 2021 AbstractIn a posteriori error analysis, the relationship between error and estimator is usually spoiled by so-called oscillation terms, which cannot be bounded by the error. In order to remedy, we devise a new approach where the oscillation has the following two properties.
Christian Kreuzer, Andreas Veeser
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Fractal and Fractional, 2023 In the current work, a fast θ scheme combined with the Legendre spectral method was developed for solving a fractional Klein–Gordon equation (FKGE). The numerical scheme was provided by the Legendre spectral method in the spatial direction, and for the ...
Yanan Li +3 more
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Analysis of the Element-Free Galerkin Method with Penalty for Stokes Problems
Entropy, 2022 The element-free Galerkin (EFG) method with penalty for Stokes problems is proposed and analyzed in this work. A priori error estimates of the penalty method, which is used to deal with Dirichlet boundary conditions, are derived to illustrate its ...
Tao Zhang, Xiaolin Li
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New View on Nonlinear Picture Fuzzy Integral Equations
Fractal and Fractional, 2023 In this article, we solve the second type of nonlinear Volterra picture fuzzy integral equation (NVPFIE) using an accelerated form of the Adomian decomposition method (ADM).
M. Shehata +3 more
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Mathematics, 2023 This study examined a Cauchy problem for a multi-dimensional Laplace equation with mixed boundary. This problem is severely ill-posed in the sense of Hadamard.
Xianli Lv, Xiufang Feng
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On King type modification of $(p,q)$-Lupaş Bernstein operators with improved estimates
Karpatsʹkì Matematičnì Publìkacìï, 2023 This paper aims to modify the $(p,q)$-Lupaş Bernstein operators using King's technique and to establish convergence results of these operators by using of modulus of continuity and Lipschitz class functions.
K.S. Nisar, V. Sharma, A. Khan
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Model Selection and Error Estimation [PDF]
Machine Learning, 2000 We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of
Peter L. Bartlett +2 more
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The error estimate and the convergence rate for h, p - refinement in the finite element analysis
Vietnam Journal of Mechanics, 2008 The goal of this study is to further investigate and to develop a more efficient way in the error estimate and the rate of the convergence for the mesh h, p-refinement procedure in the finite element analysis for two-dimensional and three-dimensional ...
Nguyen Hoai Son
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Estimation error of the constrained lasso [PDF]
2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2016 This paper presents a non-asymptotic upper bound for the estimation error of the constrained lasso, under the high-dimensional (n ≪ p) setting. In contrast to existing results, the error bound in this paper is sharp, is valid when the parameter to be estimated is not exactly sparse (e.g., when it is weakly sparse), and shows explicitly the effect of ...
Nissim Zerbib +3 more
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Error estimate in the central limit theorem
Lietuvos Matematikos Rinkinys, 2008 In this paper, we determined, independent identically distributed random variable’s {Xk, k = 1,2,...} centered and normalized sum’s Sn = \sumn k=1 Xk distribution’s Fn(x) = P(Zn < x) exact error estimate in case of the normal approximation with one ...
Aurelija Kasparavičiūtė +1 more
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