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We consider the problem of uniform sampling of points on an algebraic variety. Specifically, we develop a randomized algorithm that, given a small set of multivariate polynomials over a sufficiently large finite field, produces a common…

Data Structures and Algorithms · Computer Science 2009-02-10 Mahdi Cheraghchi , Amin Shokrollahi

Let $P_1, \ldots, P_m \in K[y]$ be polynomials with distinct degrees, no constant terms and coefficients in a general locally compact topological field $K$. We give a quantitative count of the number of polynomial progressions $x, x+P_1(y),…

Number Theory · Mathematics 2024-11-27 Ben Krause , Mariusz Mirek , Sarah Peluse , James Wright

In this paper, we introduce a method known as polynomial frame approximation for approximating smooth, multivariate functions defined on irregular domains in $d$ dimensions, where $d$ can be arbitrary. This method is simple, and relies only…

Numerical Analysis · Mathematics 2020-05-27 Ben Adcock , Daan Huybrechs

We discuss several enumerative results for irreducible polynomials of a given degree and pairs of relatively prime polynomials of given degrees in several variables over finite fields. Two notions of degree, the {\em total degree} and the…

Number Theory · Mathematics 2008-11-26 Xiang-dong Hou , Gary L. Mullen

Interpolation of data on non-Euclidean spaces is an active research area fostered by its numerous applications. This work considers the Hermite interpolation problem: finding a sufficiently smooth manifold curve that interpolates a…

Numerical Analysis · Mathematics 2024-02-27 Axel Séguin , Daniel Kressner

We consider the sparse polynomial approximation of a multivariate function on a tensor product domain from samples of both the function and its gradient. When only function samples are prescribed, weighted $\ell^1$ minimization has recently…

Numerical Analysis · Mathematics 2019-02-22 Ben Adcock , Yi Sui

It is a common contention that it is an ``impossible mission'' to exactly determine the minimum sample size for the estimation of a binomial parameter with prescribed margin of error and confidence level. In this paper, we investigate such…

Statistics Theory · Mathematics 2007-08-02 Xinjia Chen

We give a lower bound for the degree of an irreducible factor of a given polynomial. This improves and generalizes the results obtained in [4, On the irreducible factors of a polynomial, Proc. Amer. Math. Soc., 148 (2020] 1429 -- 1437].

Number Theory · Mathematics 2020-08-03 Anuj Jakhar , Srinivas Koytada

Let $\cP_n$ be the space of homogeneous polynomials of degree $n$ on $\bbR^{m+1}$. We consider the asymptotic behavior of some coefficients relating to the decomposition of $\cP_n$ into the sum of $\SO(m+1)$-irreducible components. Using…

Classical Analysis and ODEs · Mathematics 2018-02-27 V. Gichev

This paper introduces first order Sobolev spaces on certain rectifiable varifolds. These complete locally convex spaces are contained in the generally nonlinear class of generalised weakly differentiable functions and share key functional…

Classical Analysis and ODEs · Mathematics 2017-05-25 Ulrich Menne

The density of polynomials in a weighted space of infinitely differentiable functions in a multidimensional real space is proved under minimal conditions on weight functions and on differences between weight functions. We apply this result…

Classical Analysis and ODEs · Mathematics 2007-05-23 P. V. Fedotova , I. Kh. Musin

Nonlinear dimensionality reduction methods provide a valuable means to visualize and interpret high-dimensional data. However, many popular methods can fail dramatically, even on simple two-dimensional manifolds, due to problems such as…

Machine Learning · Statistics 2020-07-08 Daniel Ting , Michael I. Jordan

In the paper, the planar polynomial geometric interpolation of data points is revisited. Simple sufficient geometric conditions that imply the existence of the interpolant are derived in general. They require data points to be convex in a…

Numerical Analysis · Mathematics 2022-08-16 Jernej Kozak

We consider extremal polynomials with respect to a Sobolev-type $p$-norm, with $1<p<\infty$ and measures supported on compact subsets of the real line. For a wide class of such extremal polynomials with respect to mutually singular measures…

Classical Analysis and ODEs · Mathematics 2017-10-10 A. Diaz Gonzalez , G. Lopez Lagomasino , H. Pijeira Cabrera

Using polynomial interpolation, along with structural properties of the family of positive real rational functions, we here show that a set of m nodes in the open left half of the complex plane, can always be mapped to anywhere in the…

Optimization and Control · Mathematics 2017-04-21 Daniel Alpay , Izchak Lewkowicz

This work concerns the distance in 2-norm from a matrix polynomial to a nearest polynomial with a specified number of its eigenvalues at specified locations in the complex plane. Perturbations are allowed only on the constant coefficient…

Numerical Analysis · Mathematics 2013-06-24 Michael Karow , Emre Mengi

We introduce a numerical method for reconstructing a multidimensional surface using the gradient of the surface measured at some values of the coordinates. The method consists of defining a multidimensional spline function and minimizing…

Computational Physics · Physics 2015-05-20 Gergely Endrodi

In this work, we introduce new families of nonconforming approximation methods for reconstructing functions on general polygonal meshes. These methods are defined using degrees of freedom based on weighted moments of orthogonal polynomials…

Numerical Analysis · Mathematics 2025-08-12 Francesco Dell'Accio , Allal Guessab , Gradimir V. Milovanović , Federico Nudo

We consider the problem of stable sampling of multivariate real polynomials of large degree in a general framework where the polynomials are defined on an affine real algebraic variety $M$, equipped with a weighted measure. In particular,…

Classical Analysis and ODEs · Mathematics 2018-06-04 Robert J. Berman , Joaquim Ortega-Cerdà

Monte Carlo integration is a commonly used technique to compute intractable integrals and is typically thought to perform poorly for very high-dimensional integrals. To show that this is not always the case, we examine Monte Carlo…

Methodology · Statistics 2023-05-26 Yanbo Tang
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