Novel Step Size for Unconstrained Optimization

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.