Sufficient Conditions for Error Distance Reduction in the (\ell^2)-norm Trust Region between Minimizers of Local Nonconvex Multivariate Quadratic Approximates

Fuente: arXiv
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Main Author: Xie, Pengcheng
Format: Preprint
Published: 2023
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_version_ 1866911957285601280
author Xie, Pengcheng
author_facet Xie, Pengcheng
contents This paper analyzes the sufficient conditions for distance reduction between minimizers of local nonconvex quadratic approximate functions with diagonal Hessian in the (\ell^2)-norm trust regions after two iterations. Some examples illustrate the theoretical results of this study.
format Preprint
id arxiv_https___arxiv_org_abs_2310_08603
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Sufficient Conditions for Error Distance Reduction in the (\ell^2)-norm Trust Region between Minimizers of Local Nonconvex Multivariate Quadratic Approximates
Xie, Pengcheng
Optimization and Control
65G99, 65K05, 90C30
This paper analyzes the sufficient conditions for distance reduction between minimizers of local nonconvex quadratic approximate functions with diagonal Hessian in the (\ell^2)-norm trust regions after two iterations. Some examples illustrate the theoretical results of this study.
title Sufficient Conditions for Error Distance Reduction in the (\ell^2)-norm Trust Region between Minimizers of Local Nonconvex Multivariate Quadratic Approximates
topic Optimization and Control
65G99, 65K05, 90C30
url https://arxiv.org/abs/2310.08603