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The dominant cost in solving least-square problems using Newton's method is often that of factorizing the Hessian matrix over multiple values of the regularization parameter ($\lambda$). We propose an efficient way to interpolate the…

Machine Learning · Computer Science 2015-06-11 Da Kuang , Alex Gittens , Raffay Hamid

In this work, we address the problem of polynomial interpolation of non-pointwise data. More specifically, we assume that our input information comes from measurements obtained on diffuse compact domains. Although the nodal and the diffused…

Numerical Analysis · Mathematics 2025-09-22 Ludovico Bruni Bruno , Stefano De Marchi , Giacomo Elefante

The study of interpolation nodes and their associated Lebesgue constants are central to numerical analysis, impacting the stability and accuracy of polynomial approximations. In this paper, we will explore the Morrow-Patterson points, a set…

Numerical Analysis · Mathematics 2024-12-20 Tomasz Beberok , Leokadia Białas-Cież , Stefano De Marchi

In approximation of functions based on point values, least-squares methods provide more stability than interpolation, at the expense of increasing the sampling budget. We show that near-optimal approximation error can nevertheless be…

Numerical Analysis · Mathematics 2024-02-14 Abdellah Chkifa , Matthieu Dolbeault

In the framework of mapped pseudospectral methods, we introduce a new polynomial-type mapping function in order to describe accurately the dynamics of systems developing almost singular structures. Using error criteria related to the…

Computational Physics · Physics 2008-10-21 Adrian Alexandrescu , Alfonso Bueno-Orovio , Jose R. Salgueiro , Victor M. Perez-Garcia

In this work we develop a dynamically adaptive sparse grids (SG) method for quasi-optimal interpolation of multidimensional analytic functions defined over a product of one dimensional bounded domains. The goal of such approach is to…

Numerical Analysis · Mathematics 2015-08-06 Miroslav K. Stoyanov , Clayton G. Webster

Singular and oscillatory functions feature in numerous applications. The high-accuracy approximation of such functions shall greatly help us develop high-order methods for solving applied mathematics problems. This paper demonstrates that…

Numerical Analysis · Mathematics 2022-05-20 Congpei An , Hao-Ning Wu

A scaled Chebyshev node distribution is studied in this paper. It is proved that the node distribution is optimal for interpolation in $C_M^{s+1}[-1,1]$, the set of $(s+1)$-time differentiable functions whose $(s+1)$-th derivatives are…

Numerical Analysis · Mathematics 2013-05-28 N. S. Hoang

Only a few numerical methods can treat boundary value problems on polygonal and polyhedral meshes. The BEM-based Finite Element Method is one of the new discretization strategies, which make use of and benefits from the flexibility of these…

Numerical Analysis · Mathematics 2017-08-29 Steffen Weißer

The challenge to measure exposures regularly forces financial institutions into a choice between an overwhelming computational burden or oversimplification of risk. To resolve this unsettling dilemma, we systematically investigate replacing…

Computational Finance · Quantitative Finance 2025-07-15 Domagoj Demeterfi , Kathrin Glau , Linus Wunderlich

We calculate the minimal surface bounded by four-sided figures whose projection on a plane is a rectangle, starting with the bilinear interpolation and using, for smoothness, the Chebyshev polynomial expansion in our discretized numerical…

Mathematical Physics · Physics 2007-05-23 Sadataka Furui , Bilal Masud

In this article, we study the Fekete problem in segmental and combined nodal-segmental univariate polynomial interpolation by investigating sets of segments, or segments combined with nodes, such that the Vandermonde determinant for the…

Numerical Analysis · Mathematics 2024-03-15 Ludovico Bruni Bruno , Wolfgang Erb

An advantageous feature of piecewise constant policy timestepping for Hamilton-Jacobi-Bellman (HJB) equations is that different linear approximation schemes, and indeed different meshes, can be used for the resulting linear equations for…

Numerical Analysis · Mathematics 2016-01-21 Christoph Reisinger , Peter Forsyth

The present paper concerns filtered de la Vall\'ee Poussin (VP) interpolation at the Chebyshev nodes of the four kinds. This approximation model is interesting for applications because it combines the advantages of the classical Lagrange…

Numerical Analysis · Mathematics 2021-01-13 D. Occorsio , W. Themistoclakis

A multilevel kernel-based interpolation method, suitable for moderately high-dimensional function interpolation problems, is proposed. The method, termed multilevel sparse kernel-based interpolation (MLSKI, for short), uses both level-wise…

Numerical Analysis · Mathematics 2012-04-19 Emmanuil H. Georgoulis , Jeremy Levesley , Fazli Subhan

Image resizing is a basic tool in image processing and in literature we have many methods, based on different approaches, which are often specialized in only upscaling or downscaling. In this paper, independently of the (reduced or…

Numerical Analysis · Mathematics 2021-09-09 Donatella Occorsio , Giuliana Ramella , Woula Themistoclakis

This paper constructs unique compactly supported functions in Sobolev spaces that have minimal norm, maximal support, and maximal central value, under certain renormalizations. They may serve as optimized basis functions in interpolation or…

Numerical Analysis · Mathematics 2024-09-04 Robert Schaback

This paper explores the reconstruction of a real-valued function $f$ defined over a domain $\Omega \subset \mathbb{R}^2$ using bivariate polynomials that satisfy triangular histopolation conditions. More precisely, we assume that only the…

Numerical Analysis · Mathematics 2025-06-04 Ludovico Bruni Bruno , Francesco Dell'Accio , Wolfgang Erb , Federico Nudo

Histopolation is the approximation procedure that associates a degree $ d-1 $ polynomial $ p_{d-1} \in \mathscr{P}_{d-1} (I) $ with a locally integrable function $ f $ imposing that the integral (or, equivalently, the average) of $p$…

Numerical Analysis · Mathematics 2026-03-26 Ludovico Bruni Bruno , Stefano Serra-Capizzano

Previous works show convergence of rational Chebyshev approximants to the Pad\'e approximant as the underlying domain of approximation shrinks to the origin. In the present work, the asymptotic error and interpolation properties of rational…

Numerical Analysis · Mathematics 2024-10-08 Tobias Jawecki