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Polynomial regression is widely used and can help to express nonlinear patterns. However, considering very high polynomial orders may lead to overfitting and poor extrapolation ability for unseen data. The paper presents a method for…

Machine Learning · Computer Science 2023-08-01 Andrei Ivanov , Stefan Maria Ailuro

The purpose of the paper is to provide a characterization of the error of the best polynomial approximation of composite functions in weighted spaces. Such a characterization is essential for the convergence analysis of numerical methods…

Numerical Analysis · Mathematics 2023-08-14 Luisa Fermo , Concetta Laurita , Maria Grazia Russo

We determine the Lagrange function in Taylor polynomial approximation by solving an appropriate initial-value problem. Hence, we determine the remainder term which we then approximate by means of a natural cubic spline. This results in a…

Numerical Analysis · Mathematics 2023-03-06 J. S. C. Prentice

In some fields such as Mathematics Mechanization, automated reasoning and Trustworthy Computing etc., exact results are needed. Symbolic computations are used to obtain the exact results. Symbolic computations are of high complexity. In…

Symbolic Computation · Computer Science 2008-09-10 Yong Feng , Jingzhong Zhang , Xiaolin Qin , Xun Yuan

We present a method for constructing global analytical expressions that approximate a function over its entire range. These approximations not only mirror the original function as accurately as desired, but are purposefully created to…

High Energy Physics - Phenomenology · Physics 2024-07-09 Aviv Orly

In this paper, we study functional approximations where we choose the so-called radial basis function method and more specifically, quasi-interpolation. From the various available approaches to the latter, we form new quasi-Lagrange…

Numerical Analysis · Mathematics 2023-09-07 Martin Buhmann , Janin Jäger , Joaquín Jódar , Miguel L. Rodríguez

We present a complete algorithm for finding an exact minimal polynomial from its approximate value by using an improved parameterized integer relation construction method. Our result is superior to the existence of error controlling on…

Symbolic Computation · Computer Science 2010-01-06 Xiaolin Qin , Yong Feng , Jingwei Chen , Jingzhong Zhang

A wide range of numerical methods exists for computing polynomial approximations of solutions of ordinary differential equations based on Chebyshev series expansions or Chebyshev interpolation polynomials. We consider the application of…

Symbolic Computation · Computer Science 2014-07-11 Alexandre Benoit , Mioara Joldes , Marc Mezzarobba

We survey key techniques and results from approximation theory in the context of uniform approximations to real functions such as e^{-x}, 1/x, and x^k. We then present a selection of results demonstrating how such approximations can be used…

Data Structures and Algorithms · Computer Science 2013-09-20 Sushant Sachdeva , Nisheeth Vishnoi

The method of self-similar factor approximants is completed by defining the approximants of odd orders, constructed from the power series with the largest term of an odd power. It is shown that the method provides good approximations for…

Mathematical Physics · Physics 2009-11-13 V. I. Yukalov , E. P. Yukalova

Using a lemma of Davis on Gram matrices applied to the classical Orthogonal Polynomials to generate reproducing kernel interpolation over the classical domains for polynomials. These kernels have terms which are exact over the rational…

Numerical Analysis · Mathematics 2024-02-21 John Spitzer

In the era of big data, we first need to manage the data, which requires us to find missing data or predict the trend, so we need operations including interpolation and data fitting. Interpolation is a process to discover deducing new data…

Numerical Analysis · Mathematics 2022-08-26 Yijie Xu , Runqi Xu

Matrix functions are a central topic of linear algebra, and problems requiring their numerical approximation appear increasingly often in scientific computing. We review various limited-memory methods for the approximation of the action of…

Numerical Analysis · Mathematics 2020-10-26 Stefan Güttel , Daniel Kressner , Kathryn Lund

We describe a simple analytical method for effective summation of series, including divergent series. The method is based on self-similar approximation theory resulting in self-similar root approximants. The method is shown to be general…

Mathematical Physics · Physics 2015-06-23 S. Gluzman , V. I. Yukalov

To approximate solutions of a linear differential equation, we project, via trigonometric interpolation, its solution space onto a finite-dimensional space of trigonometric polynomials and construct a matrix representation of the…

Numerical Analysis · Mathematics 2011-08-30 Oksana Bihun , Austin Bren , Michael Dyrud , Kristin Heysse

The accuracy of the numerical solution of a fractional differential equation depends on the differentiability class of the solution. The derivatives of the solutions of fractional differential equations often have a singularity at the…

Numerical Analysis · Mathematics 2015-03-11 Yuri Dimitrov

This paper introduces a new functional expansion framework that extends classical ideas beyond the Taylor series. Unlike traditional Taylor expansions based on local polynomial approximations, the proposed approach arises from exact…

Numerical Analysis · Mathematics 2026-02-03 Junping Wang

It is a classical result in rational approximation theory that certain non-smooth or singular functions, such as $|x|$ and $x^{1/p}$, can be efficiently approximated using rational functions with root-exponential convergence in terms of…

Numerical Analysis · Mathematics 2025-06-27 Kingsley Yeon , Steven B. Damelin

We consider a discrete best approximation problem formulated in the framework of tropical algebra, which deals with the theory and applications of algebraic systems with idempotent operations. Given a set of samples of input and output of…

Numerical Analysis · Mathematics 2024-11-19 Nikolai Krivulin

An algorithm for computing an analytic function of a matrix $A$ is described. The algorithm is intended for the case where $A$ has some close eigenvalues, and clusters (subsets) of close eigenvalues are separated from each other. This…

Numerical Analysis · Mathematics 2023-12-13 V. G. Kurbatov , I. V. Kurbatova