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Gaussian Processes are used in many applications to model spatial phenomena. Within this context, a key issue is to decide the set of locations where to take measurements so as to obtain a better approximation of the underlying function.…

Emerging Technologies · Computer Science 2019-01-31 Lorenzo Bottarelli , Alessandro Farinelli

In this paper, we approximate the fractional derivative of a given function using the univariate multinode Shepard method through the Gauss-Jacobi quadrature formula. Subsequently, the proposed method is applied to the numerical solution of…

Numerical Analysis · Mathematics 2025-08-12 Francesco Dell'Accio , Filomena Di Tommaso , Ilde Ferrara

In this paper, we describe a new method to compute the minimum of a real polynomial function and the ideal defining the points which minimize this polynomial function, assuming that the minimizer ideal is zero-dimensional. Our method is a…

Algebraic Geometry · Mathematics 2013-03-22 Marta Abril Bucero , Bernard Mourrain , Philippe Trebuchet

This article extends the theory of classical finite-difference summation-by-parts (FD-SBP) time-marching methods to the generalized summation-by-parts (GSBP) framework. Dual-consistent GSBP time-marching methods are shown to retain: A and…

Numerical Analysis · Mathematics 2016-01-26 Pieter D. Boom , David W. Zingg

Highly oscillatory integrals of composite type arise in electronic engineering and their calculations is a challenging problem. In this paper, we propose two Gaussian quadrature rules for computing such integrals. The first one is…

Numerical Analysis · Mathematics 2025-04-01 Menghan Wu , Haiyong Wang

We present an algorithm for minimizing a sum of functions that combines the computational efficiency of stochastic gradient descent (SGD) with the second order curvature information leveraged by quasi-Newton methods. We unify these…

Machine Learning · Computer Science 2014-12-02 Jascha Sohl-Dickstein , Ben Poole , Surya Ganguli

The purpose of this paper is to construct universal, auto--adaptive, localized, linear, polynomial (-valued) operators based on scattered data on the (hyper--)sphere $\SS^q$ ($q\ge 2$). The approximation and localization properties of our…

Numerical Analysis · Mathematics 2008-11-11 Q. T. Le Gia , H. N. Mhaskar

A relaxation method based on border basis reduction which improves the efficiency of Lasserre's approach is proposed to compute the optimum of a polynomial function on a basic closed semi algebraic set. A new stopping criterion is given to…

Algebraic Geometry · Mathematics 2015-08-25 Marta Abril Bucero , Bernard Mourrain

It is shown that quadrature formulas in many different applications can be derived from rational approximation of the Cauchy transform of a weight function. Since rational approximation is now a routine technology, this provides an easy new…

Numerical Analysis · Mathematics 2025-07-22 Andrew Horning , Lloyd N. Trefethen

Given a graphical model (GM), computing its partition function is the most essential inference task, but it is computationally intractable in general. To address the issue, iterative approximation algorithms exploring certain local…

Machine Learning · Computer Science 2019-05-15 Sejun Park , Eunho Yang , Se-Young Yun , Jinwoo Shin

In the Sobolev space $L_2^{(m)}(0,1)$ optimal quadrature formulas with the nodes (1.5) are investigated. For optimal coefficients explicit form are obtained and norm of the error functional is calculated. In particular, by choosing…

Numerical Analysis · Mathematics 2009-11-17 Kh. M. Shadimetov , A. R. Hayotov

In this contribution we deal with Gaussian quadrature rules based on orthogonal polynomials associated with a weight function $w(x)= x^{\alpha} e^{-x}$ supported on an interval $(0,z)$, $z>0.$ The modified Chebyshev algorithm is used in…

Numerical Analysis · Mathematics 2024-01-05 Juan C. García-Ardila , Francisco Marcellán

We present a general approach to rounding semidefinite programming relaxations obtained by the Sum-of-Squares method (Lasserre hierarchy). Our approach is based on using the connection between these relaxations and the Sum-of-Squares proof…

Data Structures and Algorithms · Computer Science 2013-12-24 Boaz Barak , Jonathan Kelner , David Steurer

We develop a constructive piecewise polynomial approximation theory in weighted Sobolev spaces with Muckenhoupt weights for any polynomial degree. The main ingredients to derive optimal error estimates for an averaged Taylor polynomial are…

Numerical Analysis · Mathematics 2014-11-27 Ricardo H. Nochetto , Enrique Otarola , Abner J. Salgado

The (unweighted) point-separation problem asks, given a pair of points $s$ and $t$ in the plane, and a set of candidate geometric objects, for the minimum-size subset of objects whose union blocks all paths from $s$ to $t$. Recent work has…

Computational Geometry · Computer Science 2026-02-16 Jayson Lynch , Jack Spalding-Jamieson

The Moment/Sum-of-squares hierarchy provides a way to compute the global minimizers of polynomial optimization problems (POP), at the cost of solving a sequence of increasingly large semidefinite programs (SDPs). We consider large-scale…

Optimization and Control · Mathematics 2023-09-13 Johannes Aspman , Gilles Bareilles , Vyacheslav Kungurtsev , Jakub Marecek , Martin Takáč

We analyze the convergence of higher order Quasi-Monte Carlo (QMC) quadratures of solution-functionals to countably-parametric, nonlinear operator equations with distributed uncertain parameters taking values in a separable Banach space $X$…

Numerical Analysis · Mathematics 2015-06-25 Josef Dick , Quoc T. Le Gia , Christoph Schwab

We revisit the problem of extending quadrature formulas for general weight functions, and provide a generalization of Patterson's method for the constant weight function. The method can be used to compute a nested sequence of quadrature…

Numerical Analysis · Mathematics 2016-04-22 Sanjay Mehrotra , Dávid Papp

Topology optimization of frame structures under free-vibration eigenvalue constraints constitutes a challenging nonconvex polynomial optimization problem with disconnected feasible sets. In this article, we first formulate it as a…

Optimization and Control · Mathematics 2025-09-08 Marek Tyburec , Michal Kočvara , Marouan Handa , Jan Zeman

The computation of the entries of Jacobi operators associated with orthogonal polynomials has important applications in numerical analysis. From truncating the operator to form a Jacobi matrix, one can apply the Golub--Welsh algorithm to…

Numerical Analysis · Mathematics 2013-11-25 Thomas Trogdon , Sheehan Olver
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