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We consider the problem of efficient integration of an n-variate polynomial with respect to the Gaussian measure in R^n and related problems of complex integration and optimization of a polynomial on the unit sphere. We identify a class of…

Optimization and Control · Mathematics 2007-05-23 Alexander Barvinok

We study numerical integration on the unit sphere $\mathbb{S}^2 \subset \mathbb{R}^3$ using equal weight quadrature rules, where the weights are such that constant functions are integrated exactly. The quadrature points are constructed by…

Numerical Analysis · Mathematics 2014-02-17 Johann S. Brauchart , Josef Dick

Motivated by uncertainty quantification of complex systems, we aim at finding quadrature formulas of the form $\int_a^b f(x) d\mu(x) = \sum_{i=1}^n w_i f(x_i)$ where $f$ belongs to $H^1(\mu)$. Here, $\mu$ belongs to a class of continuous…

Statistics Theory · Mathematics 2022-08-01 Olivier Roustant , Nora Lüthen , Fabrice Gamboa

The purpose of this work is to introduce a strategy for determining the nodes and weights of a low-cardinality positive cubature formula nearly exact for polynomials of a given degree over spherical polygons. In the numerical section we…

Numerical Analysis · Mathematics 2024-03-12 Alvise Sommariva

We provide a robust and general algorithm for computing distribution functions associated to induced orthogonal polynomial measures. We leverage several tools for orthogonal polynomials to provide a spectrally-accurate method for a broad…

Numerical Analysis · Mathematics 2017-04-28 Akil Narayan

We obtain cubature formulas of volume potentials over bounded domains combining the basis functions introduced in the theory of approximate approximations with their integration over the tangential-halfspace. Then the computation is reduced…

Numerical Analysis · Mathematics 2012-10-29 F. Lanzara , V. Maz'ya , G. Schmidt

In lattice Quantum Field Theory, we are often presented with integrals over polynomials of coefficients of matrices in U(N) or SU(N) with respect to the Haar measure. In some physical situations, e.g., in presence of a chemical potential,…

High Energy Physics - Lattice · Physics 2016-10-07 Andreas Ammon , Tobias Hartung , Karl Jansen , Hernan Leövey , Julia Volmer

Mixture models, such as Gaussian mixture models, are widely used in machine learning to represent complex data distributions. A key challenge, especially in high-dimensional settings, is to determine the mixture order and estimate the…

Optimization and Control · Mathematics 2025-09-30 Srećko Đurašinović , Jean-Bernard Lasserre , Victor Magron

The aim of this paper is to extend the approximate quasi-interpolation on a uniform grid by dilated shifts of a smooth and rapidly decaying function on a uniform grid to scattered data quasi-interpolation. It is shown that high order…

Numerical Analysis · Mathematics 2007-05-23 F. Lanzara , V. Maz'ya , G. Schmidt

We discuss a cheap and stable approach to polynomial moment-based compression of multivariate measures by discrete signed measures. The method is based on the availability of an orthonormal basis and a low-cardinality algebraic quadrature…

Numerical Analysis · Mathematics 2025-10-28 Laura Rinaldi , Alvise Sommariva , Marco Vianello

We introduce a new type of quadrature, known as approximate Gaussian quadrature (AGQ) rules using {\epsilon}-quasiorthogonality, for the approximation of integrals of the form \int f(x)d \alpha(x). The measure {\alpha}(\cdot) can be…

Numerical Analysis · Mathematics 2018-11-13 Pierre-David Létourneau , Eric Darve

In molecular physics, it is often necessary to average over the orientation of molecules when calculating observables, in particular when modelling experiments in the liquid or gas phase. Evaluated in terms of Euler angles, this is closely…

Computational Physics · Physics 2024-10-23 Alexander Blech , Raoul M. M. Ebeling , Marec Heger , Christiane P. Koch , Daniel M. Reich

The purpose of this article is twofold. On the one hand, we prove asymptotic formulas for the quantitative distribution of rational points on any smooth non-split projective quadratic surface. We obtain the optimal error term for the real…

Number Theory · Mathematics 2025-01-29 Zhizhong Huang , Damaris Schindler , Alec Shute

We take a unifying and new approach toward polynomial and trigonometric approximation in an arbitrary number of variables, resulting in a precise and general ready-to-use tool that anyone can easily apply in new situations of interest. The…

Classical Analysis and ODEs · Mathematics 2023-05-31 Marcel de Jeu

An infinitely wide model is a weighted integration $\int \varphi(x,v) d \mu(v)$ of feature maps. This model excels at handling an infinite number of features, and thus it has been adopted to the theoretical study of deep learning. Kernel…

Machine Learning · Statistics 2020-07-08 Sho Sonoda

In this paper, we address the problem of approximating a multivariate function defined on a general domain in $d$ dimensions from sample points. We consider weighted least-squares approximation in an arbitrary finite-dimensional space $P$…

Numerical Analysis · Mathematics 2019-12-17 Ben Adcock , Juan M. Cardenas

We analyze the accuracy of the discrete least-squares approximation of a function $u$ in multivariate polynomial spaces $\mathbb{P}_\Lambda:={\rm span} \{y\mapsto y^\nu \,: \, \nu\in \Lambda\}$ with $\Lambda\subset \mathbb{N}_0^d$ over the…

Numerical Analysis · Mathematics 2016-10-25 Albert Cohen , Giovanni Migliorati , Fabio Nobile

The present paper is devoted to construction of an optimal quadrature formula for approximation of Fourier integrals in the Hilbert space $W_2^{(1,0)}[a,b]$ of non-periodic, complex valued functions. Here the quadrature sum consists of…

Numerical Analysis · Mathematics 2021-02-16 Samandar S. Babaev , A. R. Hayotov , U. N. Khayriev

Binary embedding is the problem of mapping points from a high-dimensional space to a Hamming cube in lower dimension while preserving pairwise distances. An efficient way to accomplish this is to make use of fast embedding techniques…

Data Structures and Algorithms · Computer Science 2016-03-15 Samet Oymak

The rate of convergence of weighted kernel herding (WKH) and sequential Bayesian quadrature (SBQ), two kernel-based sampling algorithms for estimating integrals with respect to some target probability measure, is investigated. Under…

Machine Learning · Statistics 2021-11-02 Rajiv Khanna , Liam Hodgkinson , Michael W. Mahoney