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We consider regular polynomial interpolation algorithms on recursively defined sets of interpolation points which approximate global solutions of arbitrary well-posed systems of linear partial differential equations. Convergence of the…

Numerical Analysis · Mathematics 2008-07-10 Joerg Kampen

In this work, a new technique has been presented to find approximate solution of linear integro-differential equations. The method is based on modified orthonormal Bernoulli polynomials and an operational matrix thereof. The method converts…

Numerical Analysis · Mathematics 2020-08-04 Udaya Pratap Singh

Approximate vanishing ideal is a concept from computer algebra that studies the algebraic varieties behind perturbed data points. To capture the nonlinear structure of perturbed points, the introduction of approximation to exact vanishing…

Machine Learning · Statistics 2019-11-11 Hiroshi Kera , Yoshihiko Hasegawa

In this paper, we propose a sparse spectral-Galerkin approximation scheme for solving the second-order partial differential equations on an arbitrary tetrahedron. Generalized Koornwinder polynomials are introduced on the reference…

Numerical Analysis · Mathematics 2021-05-18 Lueling Jia , Huiyuan Li , Zhimin Zhang

The problem of minimization of the sum of two convex functions has various theoretical and real-world applications. One of the popular methods for solving this problem is the proximal gradient method (proximal forward-backward algorithm). A…

Optimization and Control · Mathematics 2019-11-12 Daniel Reem , Simeon Reich , Alvaro De Pierro

In this paper we study nonconvex penalization using Bernstein functions whose first-order derivatives are completely monotone. The Bernstein function can induce a class of nonconvex penalty functions for high-dimensional sparse estimation…

Machine Learning · Statistics 2015-10-30 Zhihua Zhang

Solving inverse and optimization problems over solutions of nonlinear partial differential equations (PDEs) on complex spatial domains is a long-standing challenge. Here we introduce a method that parameterizes the solution using spectral…

Numerical Analysis · Mathematics 2025-10-30 James V. Roggeveen , Michael P. Brenner

Submodular function minimization is a fundamental optimization problem that arises in several applications in machine learning and computer vision. The problem is known to be solvable in polynomial time, but general purpose algorithms have…

Machine Learning · Computer Science 2015-02-10 Alina Ene , Huy L. Nguyen

We introduce an algebraic multiscale method for two--dimensional problems. The method uses the generalized multiscale finite element method based on the quadrilateral nonconforming finite element spaces. Differently from the…

Numerical Analysis · Mathematics 2022-01-27 Kanghun Cho , Imbunm Kim , Raehyun Kim , Dongwoo Sheen

Binary optimization, a representative subclass of discrete optimization, plays an important role in mathematical optimization and has various applications in computer vision and machine learning. Usually, binary optimization problems are…

Optimization and Control · Mathematics 2021-05-18 Huan Xiong , Mengyang Yu , Li Liu , Fan Zhu , Fumin Shen , Ling Shao

A polynomial matrix inequality is a formula asserting that a polynomial matrix is positive semidefinite. Polynomial matrix optimization concerns minimizing the smallest eigenvalue of a symmetric polynomial matrix subject to a tuple of…

Optimization and Control · Mathematics 2025-06-06 Jared Miller , Jie Wang , Feng Guo

We consider the pointwise weighted approximation by Bernstein operators with inner singularities. The related weight functions are weights $\bar{w}(x)=|x-\xi|^\alpha(0<\xi<1,\ \alpha>0).$ In this paper we give direct and inverse results of…

Functional Analysis · Mathematics 2011-05-25 Wen-ming Lu , Lin Zhang

We address the problem of constructing approximations based on orthogonal polynomials that preserve an arbitrary set of moments of a given function without loosing the spectral convergence property. To this aim, we compute the constrained…

Numerical Analysis · Mathematics 2025-04-18 Tino Laidin , Lorenzo Pareschi

We present an efficient framework for solving algebraically-constrained global non-convex polynomial optimization problems over subsets of the hypercube. We prove the existence of an equivalent nonlinear reformulation of such problems that…

Optimization and Control · Mathematics 2024-09-05 Mitchell Tong Harris , Pierre-David Letourneau , Dalton Jones , M. Harper Langston

We consider N-fold 4-block decomposable integer programs, which simultaneously generalize N-fold integer programs and two-stage stochastic integer programs with N scenarios. In previous work [R. Hemmecke, M. Koeppe, R. Weismantel, A…

Optimization and Control · Mathematics 2017-01-03 Raymond Hemmecke , Matthias Köppe , Robert Weismantel

We give formulas for the multiplicity of any affine isolated zero of a generic polynomial system of n equations in n unknowns with prescribed sets of monomials. First, we consider sets of supports such that the origin is an isolated root of…

Algebraic Geometry · Mathematics 2018-08-16 María Isabel Herrero , Gabriela Jeronimo , Juan Sabia

Arithmetic combinatorics is often concerned with the problem of bounding the behaviour of arbitrary finite sets in a group or ring with respect to arithmetic operations such as addition or multiplication. Similarly, combinatorial geometry…

Combinatorics · Mathematics 2014-04-01 Terence Tao

In this work, our aim is to obtain conditions to assure polynomial approximation in Hilbert spaces $L^{2}(\mu)$, with $\mu$ a compactly supported measure in the complex plane, in terms of properties of the associated moment matrix to the…

Functional Analysis · Mathematics 2019-10-28 Carmen Escribano , Raquel Gonzalo , Emilio Torrano

In this work, an efficient approximation scheme has been proposed for getting accurate approximate solution of nonlinear partial differential equations with constant or variable coefficients satisfying initial conditions in a series of…

Analysis of PDEs · Mathematics 2020-09-04 Prakash Kumar Das , M. M. Panja

Simple inequalities are established for some integrals involving the modified Bessel functions of the first and second kind. In most cases, we show that we obtain the best possible constant or that our bounds are tight in certain limits. We…

Classical Analysis and ODEs · Mathematics 2018-02-09 Robert E. Gaunt