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The task of approximating a function of d variables from its evaluations at a given number of points is ubiquitous in numerical analysis and engineering applications. When d is large, this task is challenged by the so-called curse of…

Numerical Analysis · Mathematics 2016-12-21 Albert Cohen , Giovanni Migliorati

We propose a new algorithm to the problem of polygonal curve approximation based on a multiresolution approach. This algorithm is suboptimal but still maintains some optimality between successive levels of resolution using dynamic…

Computer Vision and Pattern Recognition · Computer Science 2007-05-23 Pierre-François Marteau , Gilbas Ménier

In this paper we find extremal one-sided approximations of exponential type for a class of truncated and odd functions with a certain exponential subordination. These approximations optimize the $L^1(\mathbb{R}, |E(x)|^{-2}dx)$-error, where…

Classical Analysis and ODEs · Mathematics 2021-09-30 Emanuel Carneiro , Felipe Gonçalves

We seek random versions of some classical theorems on complex approximation by polynomials and rational functions, as well as investigate properties of random compact sets in connection to complex approximation.

Complex Variables · Mathematics 2017-09-26 Simon St-Amant , Jérémie Turcotte

The problem of biclustering consists of the simultaneous clustering of rows and columns of a matrix such that each of the submatrices induced by a pair of row and column clusters is as uniform as possible. In this paper we approximate the…

Data Structures and Algorithms · Computer Science 2008-08-22 Kai Puolamäki , Sami Hanhijärvi , Gemma C. Garriga

A set of piecewise linear functions, called polylines, $P_1,\ldots,P_L$ each with at most $n$ vertices can be simplified into a polyline $M$ with $k$ vertices, such that the Fr\'echet distances $\epsilon_1,\ldots,\epsilon_L$ to each of…

Computational Geometry · Computer Science 2021-08-30 Sepideh Aghamolaei , Mohammad Ghodsi

We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functionals. We prove that the new algorithm is convergent if the functions considered are smooth enough, under a general assumption on the spectral…

Numerical Analysis · Mathematics 2012-07-17 Erwan Faou , Fabio Nobile , Christophe Vuillot

We investigate the problem of approximating an incomplete preference relation $\succsim$ on a finite set by a complete preference relation. We aim to obtain this approximation in such a way that the choices on the basis of two preferences,…

Theoretical Economics · Economics 2023-11-14 Hiroki Nishimura , Efe A. Ok

The approximate degree of a Boolean function is the minimum degree of real polynomial that approximates it pointwise. For any Boolean function, its approximate degree serves as a lower bound on its quantum query complexity, and generically…

Computational Complexity · Computer Science 2023-05-23 Mark Bun , Nadezhda Voronova

We give a deterministic method of quasi-polynomial complexity to approximate the volume of the intersection of the unit hypercube with two specific sets. The method can actually be applied (without losing the quasi-polynomial complexity) to…

Optimization and Control · Mathematics 2024-08-30 Marius Costandin

We investigate the problem of computing a minimum set of solutions that approximates within a specified accuracy $\epsilon$ the Pareto curve of a multiobjective optimization problem. We show that for a broad class of bi-objective problems…

Data Structures and Algorithms · Computer Science 2008-05-20 Ilias Diakonikolas , Mihalis Yannakakis

Motivated by numerical methods for solving parametric partial differential equations, this paper studies the approximation of multivariate analytic functions by algebraic polynomials. We introduce various anisotropic model classes based on…

Numerical Analysis · Mathematics 2020-01-17 Andrea Bonito , Ronald DeVore , Diane Guignard , Peter Jantsch , Guergana Petrova

For a continuous function $f$ defined on a closed and bounded domain, there is at least one maximum and one minimum. First, we introduce some preliminaries which are necessary through the paper. We then present an algorithm, which is…

Numerical Analysis · Mathematics 2021-08-31 Fatih Idiz

The sparse polynomial approximation of continuous functions has emerged as a prominent area of interest in function approximation theory in recent years. A key challenge within this domain is the accurate estimation of approximation errors.…

Numerical Analysis · Mathematics 2025-06-10 Renzhong Feng , Bowen Zhang

This paper is concerned with near-optimal approximation of a given function $f \in L_2([0,1])$ with elements of a polynomially enriched wavelet frame, a so-called quarklet frame. Inspired by $hp$-approximation techniques of Binev, we use…

Numerical Analysis · Mathematics 2023-01-11 Stephan Dahlke , Marc Hovemann , Thorsten Raasch , Dorian Vogel

We strengthen the Weierstrass approximation theorem by proving that any real-valued continuous function on an interval $I \subset \mathbb{R}$ can be uniformly approximated by a real-valued polynomial whose only (possibly complex) critical…

Classical Analysis and ODEs · Mathematics 2025-01-07 David L. Bishop

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

Building on the blueprint from Goemans and Williamson (1995) for the Max-Cut problem, we construct a polynomial-time approximation algorithm for orthogonally constrained quadratic optimization problems. First, we derive a semidefinite…

Optimization and Control · Mathematics 2026-03-17 Ryan Cory-Wright , Jean Pauphilet

Let $X$ be a set of points in $\mathbb{R}^2$ and $\mathcal{O}$ be a set of geometric objects in $\mathbb{R}^2$, where $|X| + |\mathcal{O}| = n$. We study the problem of computing a minimum subset $\mathcal{O}^* \subseteq \mathcal{O}$ that…

Computational Geometry · Computer Science 2024-03-04 Timothy M. Chan , Qizheng He , Jie Xue

An important observation in compressed sensing is that the $\ell_0$ minimizer of an underdetermined linear system is equal to the $\ell_1$ minimizer when there exists a sparse solution vector and a certain restricted isometry property…

Numerical Analysis · Mathematics 2020-06-23 Yuji Nakatsukasa , Alex Townsend