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Matrix rank minimization problems are gaining a plenty of recent attention in both mathematical and engineering fields. This class of problems, arising in various and across-discipline applications, is known to be NP-hard in general. In…

Optimization and Control · Mathematics 2010-10-06 Yun-Bin Zhao

This work investigates a new approach to find closed form analytical approximate solution of linear initial value problems. Classical Bernoulli polynomials have been used to derive a finite set of orthonormal polynomials and a finite…

Numerical Analysis · Mathematics 2020-07-27 Udaya Pratap Singh

We study the problem of approximating an unknown function $f:\mathbb{R}\to\mathbb{R}$ by a degree-$d$ polynomial using as few function evaluations as possible, where error is measured with respect to a probability distribution $\mu$.…

Data Structures and Algorithms · Computer Science 2025-08-11 Chris Camaño , Raphael A. Meyer , Kevin Shu

In this note, we investigate how well we can reconstruct the best rank-$r$ approximation of a large matrix from a small number of its entries. We show that even if a data matrix is of full rank and cannot be approximated well by a low-rank…

Methodology · Statistics 2021-11-12 Shun Xu , Ming Yuan

This paper presents an alternative approach to simplify the proofs of some important results related to polynomial mappings in Computational Algebraic Geometry such as Polynomial Implicitization, Image Closure and some properties of the…

Algebraic Geometry · Mathematics 2011-11-30 Yongbi Li

Given a list of N numbers, the maximum can be computed in N iterations. During these N iterations, the maximum gets updated on average as many times as the Nth harmonic number. We first use this fact to approximate the Nth harmonic number…

Data Structures and Algorithms · Computer Science 2017-04-24 Ali Dasdan

This paper presents a method for computing eigenvalues and eigenvectors for some types of nonlinear eigenvalue problems. The main idea is to approximate the functions involved in the eigenvalue problem by rational functions and then apply a…

Numerical Analysis · Mathematics 2020-06-11 Yousef Saad , Mohamed El-Guide , Agnieszka Międlar

This paper deals with the use of numerical methods based on random root sampling techniques to solve some theoretical problems arising in the analysis of polynomials. These methods are proved to be practical and give solutions where…

Numerical Analysis · Mathematics 2025-04-15 Yousra Gati , Vladimir Petrov Kostov , Mohamed Chaouki Tarchi

We present a new algorithm for solving the real roots of a bivariate polynomial system $\Sigma=\{f(x,y),g(x,y)\}$ with a finite number of solutions by using a zero-matching method. The method is based on a lower bound for bivariate…

Symbolic Computation · Computer Science 2010-01-19 Xiaolin Qin , Yong Feng , Jingwei Chen , Jingzhong Zhang

Based on the characterization of the polyconvex envelope of isotropic functions by their signed singular value representations, we propose a simple algorithm for the numerical approximation of the polyconvex envelope. Instead of operating…

Numerical Analysis · Mathematics 2023-07-31 Timo Neumeier , Malte A. Peter , Daniel Peterseim , David Wiedemann

The Fast Reciprocal Square Root Algorithm is a well-established approximation technique consisting of two stages: first, a coarse approximation is obtained by manipulating the bit pattern of the floating point argument using integer…

Numerical Analysis · Mathematics 2023-07-31 Mike Day

We relate a previous result of ours on families of Diophantine equations having only trivial solutions with a result on the approximation of an algebraic number by products of rational numbers and units. We compare this approximation with a…

Number Theory · Mathematics 2013-12-30 Claude Levesque , Michel Waldschmidt

Approximation algorithms for classical constraint satisfaction problems are one of the main research areas in theoretical computer science. Here we define a natural approximation version of the QMA-complete local Hamiltonian problem and…

Quantum Physics · Physics 2016-10-25 Sevag Gharibian , Julia Kempe

We give a fully polynomial randomized approximation scheme to compute a lower bound for the matching polynomial of any weighted graph at a positive argument. For the matching polynomial of complete bipartite graphs with bounded weights…

Computational Complexity · Computer Science 2007-05-23 Shmuel Friedland

We consider the problem of minimizing a linear function over an affine section of the cone of positive semidefinite matrices, with the additional constraint that the feasible matrix has prescribed rank. When the rank constraint is active,…

Systems and Control · Computer Science 2016-11-22 Simone Naldi

Given a multivariate real (or complex) polynomial $p$ and a domain $\cal D$, we would like to decide whether an algorithm exists to evaluate $p(x)$ accurately for all $x \in {\cal D}$ using rounded real (or complex) arithmetic. Here…

Numerical Analysis · Mathematics 2007-05-23 James Demmel , Ioana Dumitriu , Olga Holtz

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

This paper is concerned with certifying that a given point is near an exact root of an overdetermined or singular polynomial system with rational coefficients. The difficulty lies in the fact that consistency of overdetermined systems is…

Symbolic Computation · Computer Science 2014-08-13 Tulay Ayyildiz Akoglu , Jonathan D. Hauenstein , Agnes Szanto

In this paper we introduce a family of rational approximations of the reciprocal of a $\phi$-function involved in the explicit solutions of certain linear differential equations, as well as in integration schemes evolving on manifolds. The…

Numerical Analysis · Mathematics 2021-05-18 Paola Boito , Yuli Eidelman , Luca Gemignani

Given an approximation algorithm $A$, we want to find the input with the worst approximation ratio, i.e., the input for which $A$'s output's objective value is the worst possible compared to the optimal solution's objective value. Such hard…

Data Structures and Algorithms · Computer Science 2025-04-29 Eklavya Sharma
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