Novel Step Size for Unconstrained Optimization

The step length size is the basis of gradient descent method with the desirable conjugate property. The aim of this document is to present a fresh gradient descent technique that calculates the step size based on a basic estimation of the Hessian of the function being minimized. The algorithm that results falls within the category of gradient descent methods with linear convergence characteristics. Our study includes numerical data that demonstrates the significant advantages of our approach compared to traditional gradient descent methods.

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Publication Details

Journal
Advances in Nonlinear Variational Inequalities
Published
2024-08-23
DOI
https://doi.org/10.52783/anvi.v27.964
Primary Topic
Advanced Optimization Algorithms Research
Type
article
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article

Novel Step Size for Unconstrained Optimization

Yoksal A. Laylani
Advances in Nonlinear Variational Inequalities
Advanced Optimization Algorithms Research
article

Novel Step Size for Unconstrained Optimization

Yoksal A. Laylani
article en

Abstract

The step length size is the basis of gradient descent method with the desirable conjugate property. The aim of this document is to present a fresh gradient descent technique that calculates the step size based on a basic estimation of the Hessian of the function being minimized. The algorithm that results falls within the category of gradient descent methods with linear convergence characteristics. Our study includes numerical data that demonstrates the significant advantages of our approach compared to traditional gradient descent methods.

Advances in Nonlinear Variational InequalitiesVol. 27(2)
Openalex Percentile: Top 68%
Advanced Optimization Algorithms Research
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Novel Step Size for Unconstrained Optimization — Yoksal A. Laylani · Advances in Nonlinear Variational Inequalities (2024) | TGRS Research Map | TGRS