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A deep approximation is an approximating function defined by composing more than one layer of simple functions. We study deep approximations of functions of one variable using layers consisting of low-degree polynomials or simple conformal…

Numerical Analysis · Mathematics 2025-04-25 Kingsley Yeon

D. Leviatan has investigated the behavior of the higher order derivatives of approximation polynomials of the differentiable function $f$ on $[-1,1]$. Especially, when $P_n$ is the best approximation of $f$, he estimates the differences…

Classical Analysis and ODEs · Mathematics 2014-03-04 Hee Sun Jung , Ryozi Sakai

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

Chebyshev polynomials of the first and second kind for a set K are monic polynomials with minimal L $\infty$-and L 1-norm on K, respectively. This articles presents numerical procedures based on semidefinite programming to compute these…

Optimization and Control · Mathematics 2019-03-12 Simon Foucart , Jean-Bernard Lasserre

Approximating a univariate function on the interval $[-1,1]$ with a polynomial is among the most classical problems in numerical analysis. When the function evaluations come with noise, a least-squares fit is known to reduce the effect of…

Numerical Analysis · Mathematics 2025-07-08 Takeru Matsuda , Yuji Nakatsukasa

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 establish a new extremal property of the classical Chebyshev polynomials in the context of best rank-one approximation of tensors. We also give some necessary conditions for a tensor to be a minimizer of the ratio of spectral and…

Algebraic Geometry · Mathematics 2020-03-12 Andrei Agrachev , Khazhgali Kozhasov , André Uschmajew

We consider the problem of maximizing the sum of squares of the leading coefficients of polynomials $P_{i_1}(x),\ldots ,P_{i_m}(x)$ (where $P_j(x)$ is a polynomial of degree $j$) under the restriction that the sup-norm of $\sum_{j=1}^m…

Classical Analysis and ODEs · Mathematics 2009-09-25 Holger Dette

The estimates of the uniform norm of the Chebyshev polynomial associated with a compact set $K$ consisting of a finite number of continua in the complex plane are established. These estimates are exact (up to a constant factor) in the case…

Complex Variables · Mathematics 2014-04-15 V. V. Andrievskii

Given $n$ polynomials $p_1, \dots, p_n$ of degree at most $n$ with $\|p_i\|_\infty \le 1$ for $i \in [n]$, we show there exist signs $x_1, \dots, x_n \in \{-1,1\}$ so that \[\Big\|\sum_{i=1}^n x_i p_i\Big\|_\infty < 30\sqrt{n}, \] where…

Classical Analysis and ODEs · Mathematics 2020-09-30 Victor Reis

We construct explicit easily implementable polynomial approximations of sufficiently high accuracy for locally constant functions on the union of disjoint segments. This problem has important applications in several areas of numerical…

Functional Analysis · Mathematics 2023-11-29 Yuri Malykhin , Konstantin Ryutin

We derive a three-term recurrence relation for computing the polynomial of best approximation in the uniform norm to $x^{-1}$ on a finite interval with positive endpoints. As application, we consider two-level methods for scalar elliptic…

Numerical Analysis · Mathematics 2012-05-24 Johannes K. Kraus , Panayot S. Vassilevski , Ludmil T. Zikatanov

We analyze decay of Chebyshev coefficients and local Chebyshev approximations for functions of finite regularity on finite intervals, focusing on the framework where the interval length tends to zero while the number of approximation nodes…

Numerical Analysis · Mathematics 2025-09-19 Krishna Yamanappa Poojara , Sabhrant Sachan , Ambuj Pandey

Exponential sums with monomials are highly related to many interesting problems in number theory and well studied by many literatures. In this paper, we consider the exponential sums with polynomials and prove a new upper bound. As an…

Number Theory · Mathematics 2025-10-24 Lingyu Guo , Victor Zhenyu Guo , Mengyao Jing

This paper presents a novel method for generating a single polynomial approximation that produces correctly rounded results for all inputs of an elementary function for multiple representations. The generated polynomial approximation has…

Mathematical Software · Computer Science 2022-03-18 Mridul Aanjaneya , Jay P. Lim , Santosh Nagarakatte

The multivariate integer Chebyshev problem is to find polynomials with integer coefficients that minimize the supremum norm over a compact set in $\C^d.$ We study this problem on general sets, but devote special attention to product sets…

Number Theory · Mathematics 2013-07-23 P. B. Borwein , I. E. Pritsker

Uniform polynomial approximation, also called minimax approximation or Chebyshev approximation, consists in searching polynomial approximation that minimizes the worst case error. Optimality conditions for the uniform approximation of…

Numerical Analysis · Mathematics 2026-05-29 Alexandre Goldsztejn

We consider the problem of estimating the support size of a discrete distribution whose minimum non-zero mass is at least $ \frac{1}{k}$. Under the independent sampling model, we show that the sample complexity, i.e., the minimal sample…

Statistics Theory · Mathematics 2016-12-13 Yihong Wu , Pengkun Yang

In this paper, we establish a new estimate (including lower and upper bounds) for an important quantity involved in the convergence analysis of smoothed aggregation algebraic multigrid methods. The new upper bound improves the existing…

Numerical Analysis · Mathematics 2019-03-19 Xuefeng Xu , Chen-Song Zhang

The approximate degree of a Boolean function $f(x_{1},x_{2},\ldots,x_{n})$ is the minimum degree of a real polynomial that approximates $f$ pointwise within $1/3$. Upper bounds on approximate degree have a variety of applications in…

Computational Complexity · Computer Science 2018-01-16 Alexander A. Sherstov