Using generalized simplex methods to approximate derivatives

Fuente: arXiv
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Auteurs principaux: Jarry-Bolduc, Gabriel, Planiden, Chayne
Format: Preprint
Publié: 2023
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author Jarry-Bolduc, Gabriel
Planiden, Chayne
author_facet Jarry-Bolduc, Gabriel
Planiden, Chayne
contents This paper presents two methods for approximating a proper subset of the entries of a Hessian using only function evaluations. These approximations are obtained using the techniques called \emph{generalized simplex Hessian} and \emph{generalized centered simplex Hessian}. We show how to choose the matrices of directions involved in the computation of these two techniques depending on the entries of the Hessian of interest. We discuss the number of function evaluations required in each case and develop a general formula to approximate all order-$P$ partial derivatives. Since only function evaluations are required to compute the methods discussed in this paper, they are suitable for use in derivative-free optimization methods.
format Preprint
id arxiv_https___arxiv_org_abs_2310_16997
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Using generalized simplex methods to approximate derivatives
Jarry-Bolduc, Gabriel
Planiden, Chayne
Numerical Analysis
This paper presents two methods for approximating a proper subset of the entries of a Hessian using only function evaluations. These approximations are obtained using the techniques called \emph{generalized simplex Hessian} and \emph{generalized centered simplex Hessian}. We show how to choose the matrices of directions involved in the computation of these two techniques depending on the entries of the Hessian of interest. We discuss the number of function evaluations required in each case and develop a general formula to approximate all order-$P$ partial derivatives. Since only function evaluations are required to compute the methods discussed in this paper, they are suitable for use in derivative-free optimization methods.
title Using generalized simplex methods to approximate derivatives
topic Numerical Analysis
url https://arxiv.org/abs/2310.16997