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This paper deals with the evaluation of double line integrals of the squared exponential covariance function. We propose a new approach in which the double integral is reduced to a single integral using the error function. This single…

Machine Learning · Statistics 2018-12-19 J. N. Hendriks , C. Jidling , A. Wills , T. B. Schön

This paper compares two basic approaches to solving ordinary differential equations, which form the basis for attitude computation in strapdown inertial navigation systems, namely, the Taylor series expansion approach that was used in its…

Numerical Analysis · Mathematics 2021-09-21 Yuanxin Wu , Yury A. Litmanovich

We propose a high-order FDTD scheme based on the correction function method (CFM) to treat interfaces with complex geometry without increasing the complexity of the numerical approach for constant coefficients. Correction functions are…

Numerical Analysis · Mathematics 2020-02-18 Yann-Meing Law , Alexandre Noll Marques , Jean-Christophe Nave

This study explores various feature selection techniques applied to macro-economic forecasting, using Iran's World Bank Development Indicators. Employing a comprehensive evaluation framework that includes Root Mean Square Error (RMSE) and…

General Economics · Economics 2024-11-06 Mahdi Goldani

The aim of this paper is to establish various factorization results and then to derive estimates for linear functionals through the use of a generalized Taylor theorem. Additionally, several error bounds are established including…

Classical Analysis and ODEs · Mathematics 2024-12-10 Ali Hasan Ali , Zsolt Páles

In this work a general approach to compute a compressed representation of the exponential $\exp(h)$ of a high-dimensional function $h$ is presented. Such exponential functions play an important role in several problems in Uncertainty…

Numerical Analysis · Mathematics 2023-02-22 Martin Eigel , Nando Farchmin , Sebastian Heidenreich , Philipp Trunschke

A new algorithm for eigenvalue problems for the fractional Jacobi type ODE is proposed. The algorithm is based on piecewise approximation of the coefficients of the differential equation with subsequent recursive procedure adapted from some…

Numerical Analysis · Mathematics 2018-06-27 Ivan Gavrilyuk , Volodymyr Makarov , Nataliia Romaniuk

Function calling is a core capability of large language models, essential for AI agents. Existing benchmarks such as the Berkeley Function Calling Leaderboard (BFCL), tau^2-Bench (arXiv:2506.07982), and ACEBench (arXiv:2501.12851) evaluate…

Artificial Intelligence · Computer Science 2025-09-24 Nikolai Skripko

Recovery type a posteriori error estimators are popular, particularly in the engineering community, for their computationally inexpensive, easy to implement, and generally asymptotically exactness. Unlike the residual type error estimators,…

Numerical Analysis · Mathematics 2025-03-26 Ying Liu , Jingjing Xiao , Nianyu Yi , Huihui Cao

We proposed an iterate scheme for solving convex-concave saddle-point problems associated with general convex-concave functions. We demonstrated that when our iterate scheme is applied to a special class of convex-concave functions, which…

Optimization and Control · Mathematics 2023-11-01 Hui Ouyang

The quadrature error associated with a regular quadrature rule for evaluation of a layer potential increases rapidly when the evaluation point approaches the surface and the integral becomes nearly singular. Error estimates are needed to…

Numerical Analysis · Mathematics 2022-01-20 Ludvig af Klinteberg , Chiara Sorgentone , Anna-Karin Tornberg

Policy evaluation is a crucial step in many reinforcement-learning procedures, which estimates a value function that predicts states' long-term value under a given policy. In this paper, we focus on policy evaluation with linear function…

Machine Learning · Computer Science 2017-06-12 Simon S. Du , Jianshu Chen , Lihong Li , Lin Xiao , Dengyong Zhou

This remark describes efficiency improvements to Algorithm 916 [Zaghloul and Ali 2011]. It is shown that the execution time required by the algorithm, when run at its highest accuracy, may be improved by more than a factor of two. A better…

Instrumentation and Methods for Astrophysics · Physics 2015-05-27 Mofreh R. Zaghloul

In this letter, we present a novel exponentially embedded families (EEF) based classification method, in which the probability density function (PDF) on raw data is estimated from the PDF on features. With the PDF construction, we show that…

Machine Learning · Statistics 2016-08-24 Bo Tang , Steven Kay , Haibo He , Paul M. Baggenstoss

We study multivariate $\boldsymbol{L}_{\infty}$-approximation for a weighted Korobov space of periodic functions for which the Fourier coefficients decay exponentially fast. The weights are defined, in particular, in terms of two sequences…

Numerical Analysis · Mathematics 2016-02-09 Peter Kritzer , Friedrich Pillichshammer , Henryk Wozniakowski

In computational inverse problems, it is common that a detailed and accurate forward model is approximated by a computationally less challenging substitute. The model reduction may be necessary to meet constraints in computing time when…

Methodology · Statistics 2018-02-14 Daniela Calvetti , Matthew M. Dunlop , Erkki Somersalo , Andrew M. Stuart

We present a novel generalized convolution quadrature method that accurately approximates convolution integrals. During the late 1980s, Lubich introduced convolution quadrature techniques, which have now emerged as a prevalent methodology…

Numerical Analysis · Mathematics 2023-05-19 Lehel Banjai , Matteo Ferrari

In this paper, we reinterpret quadratic Lyapunov functions as solutions to a performance estimation saddle point problem. This allows us to automatically detect the existence of such a Lyapunov function and thus numerically check that a…

Optimization and Control · Mathematics 2024-11-20 Olivier Fercoq

The paper describes a generalized iterative proportional fitting procedure which can be used for maximum likelihood estimation in a special class of the general log-linear model. The models in this class, called relational, apply to…

Computation · Statistics 2014-04-01 Anna Klimova , Tamas Rudas

In this work, we present a comprehensive framework for approximating the weakly singular power-law kernel $t^{\alpha-1}$ of fractional integral and differential operators, where $\alpha \in (0,1)$ and $t \in [\delta,T]$ with…

Numerical Analysis · Mathematics 2025-08-29 Renu Chaudhary , Kai Diethelm , Afshin Farhadi , Fred A. Fuchs