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Approximation using Fourier features is a popular technique for scaling kernel methods to large-scale problems, with myriad applications in machine learning and statistics. This method replaces the integral representation of a…

Machine Learning · Statistics 2024-08-26 Ayoub Belhadji , Qianyu Julie Zhu , Youssef Marzouk

A method of deriving quadrature rules has been developed which gives nodes and weights for a Gaussian-type rule which integrates functions of the form: f(x,y,t) = a(x,y,t)/((x-t)^2+y^2) + b(x,y,t)/([(x-t)^2+y^2]^{1/2}) +…

Numerical Analysis · Mathematics 2010-09-21 Michael Carley

Fourier feature approximations have been successfully applied in the literature for scalable Gaussian Process (GP) regression. In particular, Quadrature Fourier Features (QFF) derived from Gaussian quadrature rules have gained popularity in…

Machine Learning · Statistics 2023-10-24 Kevin Li , Max Balakirsky , Simon Mak

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

Gaussian quadrature rules are a classical tool for the numerical approximation of integrals with smooth integrands and positive weight functions. We derive and expicitly list asymptotic expressions for the points and weights of Gaussian…

Numerical Analysis · Mathematics 2022-08-25 Peter Opsomer , Daan Huybrechs

Gauss quadrature integral approximation is extended to include integrals with a measure consisting of continuous as well as discrete components. That is, we give an approximation for the integral of a function plus its sum over a discrete…

Numerical Analysis · Mathematics 2023-06-12 A. D. Alhaidari

We present bounds of quadratic form for the logarithm of the Gaussian Q-function. We also show an analytical method for deriving log-quadratic approximations of the Q-function and give an approximation with absolute error less than…

Probability · Mathematics 2013-04-10 Andrew Mastin , Patrick Jaillet

Computation of moments of transformed random variables is a problem appearing in many engineering applications. The current methods for moment transformation are mostly based on the classical quadrature rules which cannot account for the…

Methodology · Statistics 2017-01-06 Jakub Prüher , Ondřej Straka

We investigate a Gaussian quadrature rule and the corresponding orthogonal polynomials for the oscillatory weight function $e^{i\omega x}$ on the interval $[-1,1]$. We show that such a rule attains high asymptotic order, in the sense that…

Numerical Analysis · Mathematics 2012-12-07 Andreas Asheim , Alfredo Deaño , Daan Huybrechs , Haiyong Wang

This paper presents a novel systematic methodology to obtain new simple and tight approximations, lower bounds, and upper bounds for the Gaussian Q-function, and functions thereof, in the form of a weighted sum of exponential functions.…

Signal Processing · Electrical Eng. & Systems 2020-12-21 Islam M. Tanash , Taneli Riihonen

The numerical integration of an analytical function $f(x)$ using a finite set of equidistant points can be performed by quadrature formulas like the Newton-Cotes. Unlike Gaussian quadrature formulas however, higher-order Newton-Cotes…

Numerical Analysis · Mathematics 2021-08-24 Irfan Muhammad

A novel development is given of the theory of Gaussian quadrature, not relying on the theory of orthogonal polynomials. A method is given for computing the nodes and weights that is manifestly independent of choice of basis in the space of…

Numerical Analysis · Mathematics 2007-05-23 Ilan Degani , Jeremy Schiff

Gaussian Quadrature is a well known technique for numerical integration. Recently Gaussian quadrature with respect to discrete measures corresponding to finite sums have found some new interest. In this paper we apply these ideas to…

Numerical Analysis · Mathematics 2007-05-23 Hartmut Monien

The numerical evaluation of integrals of the form \begin{align*} \int_a^b f(x) e^{ikg(x)}\,dx \end{align*} is an important problem in scientific computing with significant applications in many branches of applied mathematics, science and…

Numerical Analysis · Mathematics 2024-09-02 Akash Anand , Damini Dhiman

Let $d$ and $k$ be positive integers. Let $\mu$ be a positive Borel measure on $\mathbb{R}^2$ possessing finite moments up to degree $2d-1$. If the support of $\mu$ is contained in an algebraic curve of degree $k$, then we show that there…

Numerical Analysis · Mathematics 2017-10-31 Cordian Riener , Markus Schweighofer

In this paper, we introduce the Quasi-Quadratic Gradient (QQG), a novel search direction designed to accelerate the BFGS method within the quasi-Newton framework. By defining the QQG as the product of the inverse Hessian approximation and…

Optimization and Control · Mathematics 2026-04-28 John Chiang

In this work we develop the Gaussian quadrature rule for weight functions involving fractional powers, exponentials and Bessel functions of the first kind. Besides the computation based on the use of the standard and the modified Chebyshev…

Numerical Analysis · Mathematics 2021-10-12 Eleonora Denich , Paolo Novati

A class of numerical quadrature rules is derived, with equally-spaced nodes, and unit weights except at a few points at each end of the series, for which "corrections" (not using any further information about the integrand) are added to the…

History and Overview · Mathematics 2025-12-19 Gavin R. Putland

We provide the first stochastic convergence rates for a family of adaptive quadrature rules used to normalize the posterior distribution in Bayesian models. Our results apply to the uniform relative error in the approximate posterior…

Methodology · Statistics 2022-10-27 Blair Bilodeau , Alex Stringer , Yanbo Tang

The aghq package for implementing approximate Bayesian inference using adaptive quadrature is introduced. The method and software are described, and use of the package in making approximate Bayesian inferences in several challenging low-…

Computation · Statistics 2021-06-22 Alex Stringer
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