Approximation methods in function spaces characterise how well complex functions can be represented or recovered using limited information such as function values or linear measurements. Central to ...

Abstract: Nystrom approximation is one of the most popular approximation methods to accelerate kernel analysis on largescale data sets. Nystrom employs one single landmark set to ¨ obtain eigenvectors ...

This repository contains a Jupyter notebook that demonstrates how to estimate the value of π using a simple Monte Carlo method. The code generates random points in a square and determines how many ...

Abstract: This paper proposes an electric vehicle (EV) cluster aggregation method utilizing confidence-robust polyhedral inner approximation to fully leverage the flexible scheduling potential of EV ...

An important part of the marginal maximum likelihood method described previously is the computation of the integral over the random effects. The default method in PROC NLMIXED for computing this ...

Covers asymptotic evaluation of integrals (stationary phase and steepest descent), perturbation methods (regular and singular methods, and inner and outer expansions), multiple scale methods, and ...