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We study sufficient conditions on weight functions under which norm approximations by analytic polynomials are possible. The weights we study include radial, non-radial, and angular weights.

Functional Analysis · Mathematics 2022-02-09 Ali Abkar

Motivated by conforming finite element methods for elliptic problems of second order, we analyze the approximation of the gradient of a target function by continuous piecewise polynomial functions over a simplicial mesh. The main result is…

Numerical Analysis · Mathematics 2018-03-07 Andreas Veeser

Provided a special function of one variable and some of its derivatives can be accurately computed over a finite range, a method is presented to build a series of polynomial approximations of the function with a defined relative error over…

Computational Physics · Physics 2007-05-23 C. Semay

Many interesting functions arising in applications map into Riemannian manifolds. We present an algorithm, using the manifold exponential and logarithm, for approximating such functions. Our approach extends approximation techniques for…

Numerical Analysis · Mathematics 2026-01-27 Simon Jacobsson , Raf Vandebril , Joeri van der Veken , Nick Vannieuwenhoven

The problem of root mean square approximation of a square integrable function by finite linear combinations of exponential functions is considered. It is subdivided into linear and nonlinear parts. The linear approximation problem is…

Classical Analysis and ODEs · Mathematics 2014-11-11 Ruslan Sharipov

We study the problem of multivariate $L_2$-approximation of functions in a weighted Korobov space using a median lattice-based algorithm recently proposed by the authors. In the original work, the algorithm requires knowledge of the…

Numerical Analysis · Mathematics 2025-11-04 Zexin Pan , Takashi Goda , Peter Kritzer

Functional lifting methods provide a tool for approximating solutions of difficult non-convex problems by embedding them into a larger space. In this work, we investigate a mathematically rigorous formulation based on embedding into the…

Optimization and Control · Mathematics 2020-07-07 Thomas Vogt , Roland Haase , Danielle Bednarski , Jan Lellmann

In this short note we provide a quantitative version of the classical Runge approximation property for second order elliptic operators. This relies on quantitative unique continuation results and duality arguments. We show that these…

Analysis of PDEs · Mathematics 2017-08-22 Angkana Rüland , Mikko Salo

This paper introduces a novel algorithmic solution for the approximation of a given multivariate function by a nomographic function that is composed of a one-dimensional continuous and monotone outer function and a sum of univariate…

Information Theory · Computer Science 2015-07-14 Steffen Limmer , Jafar Mohammadi , Slawomir Stanczak

We develop a general framework for estimating the $L_\infty(\mathbb{T}^d)$ error for the approximation of multivariate periodic functions belonging to specific reproducing kernel Hilbert spaces (RHKS) using approximants that are…

Numerical Analysis · Mathematics 2019-09-06 Lutz Kämmerer

We give an algorithm to compute a one-dimensional shape-constrained function that best fits given data in weighted-$L_{\infty}$ norm. We give a single algorithm that works for a variety of commonly studied shape constraints including…

Data Structures and Algorithms · Computer Science 2019-05-30 David Durfee , Yu Gao , Anup B. Rao , Sebastian Wild

In functional data analysis, binary classification with one functional covariate has been extensively studied. We aim to fill in the gap of considering multivariate functional covariates in classification. In particular, we propose an…

Machine Learning · Statistics 2025-08-11 Bingfan Liu , Peijun Sang

We present a new method for approximating real-valued functions on ${\mathbb R}^+$ by linear combinations of exponential functions with complex coefficients. The approach is based on a multi-point Pad\'e approximation of the Laplace…

Numerical Analysis · Mathematics 2026-05-05 Alexey Kuznetsov , Armin Mohammadioroojeh

We study stochastic optimization problems with objective function given by the expectation of the maximum of two linear functions defined on the component random variables of a multivariate Gaussian distribution. We consider random…

Optimization and Control · Mathematics 2021-12-15 David Bergman , Carlos Cardonha , Jason Imbrogno , Leonardo Lozano

We present a lower error bound for approximating linear multivariate operators defined over Hilbert spaces in terms of the error bounds for appropriately constructed linear functionals as long as algorithms use function values. Furthermore,…

Numerical Analysis · Mathematics 2015-11-19 Erich Novak , Henryk Wozniakowski

Our main interest is the low-rank approximation of a matrix in R^m.n under a weighted Frobenius norm. This norm associates a weight to each of the (m x n) matrix entries. We conjecture that the number of approximations is at most min(m, n).…

Applications · Statistics 2013-02-05 William Rey

In the regime of bounded transportation costs, additive approximations for the optimal transport problem are reduced (rather simply) to relative approximations for positive linear programs, resulting in faster additive approximation…

Data Structures and Algorithms · Computer Science 2018-10-23 Kent Quanrud

When implementing regular enough functions (e.g., elementary or special functions) on a computing system, we frequently use polynomial approximations. In most cases, the polynomial that best approximates (for a given distance and in a given…

Mathematical Software · Computer Science 2007-05-23 Nicolas Brisebarre , Jean-Michel Muller

We calculate the least upper bounds of pointwise and uniform approximations for classes of $2\pi$-periodic functions expressible as convolutions of an arbitrary square summable kernel with functions, which belong to the unit ball of the…

Classical Analysis and ODEs · Mathematics 2017-03-28 A. S. Serdyuk , I. V. Sokolenko

The paper deals with the problem of approximating the functions of several variables by branched continued fractions, in particular, multidimensional A- and J-fractions with independent variables. A generalization of Gragg's algorithm is…

Numerical Analysis · Mathematics 2023-03-24 Roman Dmytryshyn , Serhii Sharyn
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