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In this paper we focus on efficient implementations of the Multivariate Decomposition Method (MDM) for approximating integrals of $\infty$-variate functions. Such $\infty$-variate integrals occur for example as expectations in uncertainty…

Numerical Analysis · Mathematics 2018-08-06 Alexander D. Gilbert , Frances Y. Kuo , Dirk Nuyens , Grzegorz W. Wasilkowski

We use an interpolative technique from \cite{abps} to introduce the notion of multiple $N$-separately summing operators. Our approach extends and unifies some recent results; for instance we recover the best known estimates of the…

Functional Analysis · Mathematics 2015-07-02 N. Albuquerque , D. Núñez-Alarcón , J. Santos , D. M. Serrano-Rodríguez

Point forecasting of univariate time series is a challenging problem with extensive work having been conducted. However, nonparametric probabilistic forecasting of time series, such as in the form of quantiles or prediction intervals is an…

Machine Learning · Statistics 2020-05-15 Kostas Hatalis , Shalinee Kishore

A novel method of summation for power series is developed. The method is based on the self-similar approximation theory. The trick employed is in transforming, first, a series expansion into a product expansion and in applying the…

Statistical Mechanics · Physics 2009-11-10 V. I. Yukalov , S. Gluzman , D. Sornette

In some fields such as Mathematics Mechanization, automated reasoning and Trustworthy Computing etc., exact results are needed. Symbolic computations are used to obtain the exact results. Symbolic computations are of high complexity. In…

Symbolic Computation · Computer Science 2008-09-10 Yong Feng , Jingzhong Zhang , Xiaolin Qin , Xun Yuan

The problems of computational data processing involving regression, interpolation, reconstruction and imputation for multidimensional big datasets are becoming more important these days, because of the availability of data and their widely…

Methodology · Statistics 2017-03-22 Yuri K. Shestopaloff , Alexander Y. Shestopaloff

We propose two algorithms for boosting random Fourier feature models for approximating high-dimensional functions. These methods utilize the classical and generalized analysis of variance (ANOVA) decomposition to learn low-order functions,…

Machine Learning · Computer Science 2025-06-25 Daniel Potts , Laura Weidensager

Instead of sampling a function at a single point, average sampling takes the weighted sum of function values around the point. Such a sampling strategy is more practical and more stable. In this note, we present an explicit method with an…

Information Theory · Computer Science 2014-12-23 Wenjian Chen , Haizhang Zhang

In this work, we propose an extensive numerical study on approximating the absolute value function. The methods presented in this paper compute approximants in the form of rational functions and have been proposed relatively recently, e.g.,…

Numerical Analysis · Mathematics 2020-05-07 Ion Victor Gosea , Athanasios C. Antoulas

We consider the problem of reconstructing missing data on a smooth manifold from incomplete and nonuniform samples. While classical methods for manifold approximation typically assume quasi-uniform data, their performance deteriorates…

Numerical Analysis · Mathematics 2026-04-15 David Levin

The Empirical Interpolation Method (EIM) is a greedy procedure that constructs approximate representations of two-variable functions in separated form. In its classical presentation, the two variables play a non-symmetric role. In this…

Numerical Analysis · Mathematics 2019-08-12 Fabien Casenave , Alexandre Ern , Tony Lelièvre

The multichannel trigonometric reconstruction from uniform samples was proposed recently. It not only makes use of multichannel information about the signal but is also capable to generate various kinds of interpolation formulas according…

Classical Analysis and ODEs · Mathematics 2024-12-20 Dong Cheng , Kit Ian Kou

Finding suitable points for multivariate polynomial interpolation and approximation is a challenging task. Yet, despite this challenge, there has been tremendous research dedicated to this singular cause. In this paper, we begin by…

Numerical Analysis · Mathematics 2018-05-21 Pranay Seshadri , Gianluca Iaccarino , Tiziano Ghisu

The nonlinear inverse problem of exponential data fitting is separable since the fitting function is a linear combination of parameterized exponential functions, thus allowing to solve for the linear coefficients separately from the…

Numerical Analysis · Mathematics 2023-06-13 Annie Cuyt , Wen-shin Lee

This paper provides an efficient recursive approach of the spectral Tau method to approximate the solution of system of generalized Abel-Volterra integral equations. In this regards, we first investigate the existence, uniqueness as well as…

Numerical Analysis · Mathematics 2021-07-28 S. Shahmorad , P. Mokhtary , Y. Talaei , A. Faghih

The fundamental purpose of the present work is to constitute an enhanced Euler method with adaptive inverse-quadratic and inverse-multi-quadratic radial basis function (RBF) interpolation technique to solve initial value problems. These…

Numerical Analysis · Mathematics 2023-02-21 Samala Rathan , Deepit Shah

We present an iterative framework to improve the amortized approximations of posterior distributions in the context of Bayesian inverse problems, which is inspired by loop-unrolled gradient descent methods and is theoretically grounded in…

Machine Learning · Computer Science 2023-05-16 Rafael Orozco , Ali Siahkoohi , Mathias Louboutin , Felix J. Herrmann

We construct new rational approximants of Euler's constant that improve those of Aptekarev et al. (2007) and Rivoal (2009). The approximants are given in terms of certain (mixed type) multiple orthogonal polynomials associated with the…

Number Theory · Mathematics 2025-05-28 Thomas Wolfs , Walter Van Assche

We propose a Fast Fourier Transform based Periodic Interpolation Method (FFT-PIM), a flexible and computationally efficient approach for computing the scalar potential given by a superposition sum in a unit cell of an infinitely periodic…

Numerical Analysis · Mathematics 2024-07-01 Fangzhou Ai , Vitaliy Lomakin

We develop fixed-point algorithms for the approximation of structured matrices with rank penalties. In particular we use these fixed-point algorithms for making approximations by sums of exponentials, or frequency estimation. For the basic…

Numerical Analysis · Mathematics 2016-01-07 Fredrik Andersson , Marcus Carlsson