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Let $\xi = \{x^j\}_{j=1}^n$ be a grid of $n$ points in the $d$-cube ${\II}^d:=[0,1]^d$, and $\Phi = \{\phi_j\}_{j =1}^n$ a family of $n$ functions on ${\II}^d$. We define the linear sampling algorithm $L_n(\Phi,\xi,\cdot)$ for an…

Functional Analysis · Mathematics 2010-09-23 Dinh Dũng

We investigate the rational approximation of fractional powers of unbounded positive operators attainable with a specific integral representation of the operator function. We provide accurate error bounds by exploiting classical results in…

Numerical Analysis · Mathematics 2024-03-19 Lidia Aceto , Paolo Novati

Given an $m$-tuple of weights $\vec{v}=(v_1,\dots,v_m)$, we characterize the classes of pairs $(w,\vec{v})$ involved with the boundedness properties of the multilinear fractional integral operator from…

Classical Analysis and ODEs · Mathematics 2022-05-25 Fabio Berra , Gladis Pradolini , Wilfredo Ramos

This paper presents an algorithm for solving multiobjective optimization problems involving composite functions, where we minimize a quadratic model that approximates $F(x) - F(x^k)$ and that can be derivative-free. We establish theoretical…

Optimization and Control · Mathematics 2026-01-29 V. S. Amaral , P. B. Assunção , D. R. Souza

Without Borel or Pad$\acute{e}$ techniques, we show that for a divergent series with $n!$ large-order growth factor, the set of Hypergeometric series $_{k+1}F_{k-1}$ represents suitable approximants for which there exist no free parameters.…

High Energy Physics - Theory · Physics 2021-01-22 Abouzeid M. Shalaby

Let $\omega_0,\dots,\omega_M$ be complex numbers. If $H_0,\dots,H_M$ are polynomials of degree at most $\rho_0,\dots,\rho_M$, and $G(z)=\sum_{m=0} ^M H_m(z) (1-z)^{\omega_m}$ has a zero at $z=0$ of maximal order (for the given…

Number Theory · Mathematics 2021-09-07 Michael A. Bennett , Greg Martin , Kevin O'Bryant

Given a set of $n$ sites from $\mathbb{R}^d$, each having some positive weight factor, the Multiplicatively Weighted Voronoi Diagram is a subdivision of space that associates each cell to the site whose weighted Euclidean distance is…

Computational Geometry · Computer Science 2024-03-19 Joachim Gudmundsson , Martin P. Seybold , Sampson Wong

We study optimal algorithms in adaptive sampling recovery of smooth functions defined on the unit $d$-cube ${\II}^d:= [0,1]^d$. The recovery error is measured in the quasi-norm $\|\cdot\|_q$ of $L_q := L_q(\II^d)$. For $B$ a subset in…

Functional Analysis · Mathematics 2011-03-01 Dinh Dũng

In minimization models for image recovery and data analysis problems, loss functions and linear operators are typically aggregated as an average of composite terms. Each term in the aggregate models a desired property of the ideal solution…

Optimization and Control · Mathematics 2026-02-26 Patrick L. Combettes , Diego J. Cornejo

We study spaces $\mathcal{CV}^{k}(\Omega,E)$ of $k$-times continuously partially differentiable functions on an open set $\Omega\subset\mathbb{R}^{d}$ with values in a locally convex Hausdorff space $E$. The space…

Functional Analysis · Mathematics 2020-02-05 Karsten Kruse

Recently Koivusalo, Levesley, Ward and Zhang introduced the set of simultaneously $\Phi$-badly approximable real vectors of $\mathbb{R}^m$ with respect to an approximation function $\Phi$, and determined its Hausdorff dimension for the…

Number Theory · Mathematics 2025-03-19 Johannes Schleischitz

Meshless methods approximate operators in a specific node as a weighted sum of values in its neighbours. Higher order approximations of derivatives provide more accurate solutions with better convergence characteristics, but they come at…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-12 Jon Vehovar , Miha Rot , Gregor Kosec

Let us assume that $f$ is a continuous function defined on the unit ball of $\mathbb R^d$, of the form $f(x) = g (A x)$, where $A$ is a $k \times d$ matrix and $g$ is a function of $k$ variables for $k \ll d$. We are given a budget $m \in…

Numerical Analysis · Mathematics 2012-01-18 Massimo Fornasier , Karin Schnass , Jan Vybiral

The aim of this paper is to characterize a fractal operator associated with multivariate fractal interpolation functions (FIFs) and study the several properties of this fractal operator. Further, with the help of this operator, we…

Dynamical Systems · Mathematics 2023-10-20 Amit Bawalia , Vineeta Basotia , Ajay Prajapati

This paper focuses on numerical approximation for fractional powers of elliptic operators on $2$-d manifolds. Firstly, parametric finite element method is employed to discretize the original problem. We then approximate fractional powers of…

Numerical Analysis · Mathematics 2022-07-01 Beiping Duan

In this paper, we develop a multivariate framework for approximation by max-min neural network operators. Building on the recent advances in approximation theory by neural network operators, particularly, the univariate max-min operators,…

Machine Learning · Computer Science 2026-01-14 Abhishek Yadav , Uaday Singh , Feng Dai

The joint probabilistic data association (JPDA) filter is a popular tracking methodology for problems involving well-spaced targets, but it is rarely applied in problems with closely-spaced targets due to its complexity in these cases, and…

Systems and Control · Computer Science 2014-12-16 Jason L. Williams

Let $\{w_{i,j}\}_{1\leq i\leq n, 1\leq j\leq s} \subset L_m=F(X_1,...,X_m)[{\partial \over \partial X_1},..., {\partial \over \partial X_m}]$ be linear partial differential operators of orders with respect to ${\partial \over \partial…

Symbolic Computation · Computer Science 2007-05-23 Dima Grigoriev

We give a polynomial-time constant-factor approximation algorithm for maximum independent set for (axis-aligned) rectangles in the plane. Using a polynomial-time algorithm, the best approximation factor previously known is $O(\log\log n)$.…

Computational Geometry · Computer Science 2021-07-07 Joseph S. B. Mitchell

When implementing regular enough functions (e.g., elementary or special functions) on a computing system, we frequently use polynomial approximations. In most cases, the polynomial that best approximates (for a given distance and in a given…

Mathematical Software · Computer Science 2007-05-23 Nicolas Brisebarre , Jean-Michel Muller