Over the last two decades, it has been observed that using the gradient vector as a search
direction in large-scale optimization may lead to efficient algorithms. The effectiveness relies …

A fully derivative-free spectral residual method for solving large-scale nonlinear systems of
equations is presented. It uses in a systematic way the residual vector as a search direction …

Combined with non‐monotone line search, the Barzilai and Borwein (BB) gradient method
has been successfully extended for solving unconstrained optimization problems and is …

A review is given of the underlying theory and recent developments in regard to the Barzilai-
Borwein steepest descent method for large scale unconstrained optimization. One aim is to …

A generalization of the steepest descent and other methods for solving a large scale
symmetric positive definitive system Ax= b is presented. Given a positive integer m, the new …

In this paper we propose new globalization strategies for the Barzilai and Borwein gradient
method, based on suitable relaxations of the monotonicity requirements. In particular, we …

This study presents SPFSR, a novel stochastic approximation approach for performing
simultaneous k-best feature ranking (FR) and feature selection (FS) based on Simultaneous …

The possibilities inherent in steepest descent methods have been considerably amplified by
the introduction of the Barzilai–Borwein choice of step-size, and other related ideas. These …

We introduced an algorithm for unconstrained optimization based on the transformation of
the Newton method with the line search into a gradient descent method. Main idea used in …

We present a gradient descent algorithm with a line search procedure for solving
unconstrained optimization problems which is defined as a result of applying Picard-Mann …