<abstract xmlns="http://www.w3.org/1999/xhtml"><p>An accelerated of the steepest descent method for solving unconstrained optimization problems is presented. which propose a fundamentally different conjugate gradient method, in which the well-known parameter <italic>β<sub>k</sub></italic> is computed by an new formula. Under common assumptions, by using a modified Wolfe line search, descent property and global convergence results were established for the new method. Experimental results provide evidence that our proposed method is in general superior to the classical steepest descent method and has a potential to significantly enhance the computational efficiency and robustness of the training process.</p></abstract>

An accelerated of the steepest descent method for solving unconstrained optimization problems is presented. which propose a fundamentally different conjugate gradient method, in which the well-known parameter βk is computed by an new formula. Under common assumptions, by using a modified Wolfe line search, descent property and global convergence results were established for the new method. Experimental results provide evidence that our proposed method is in general superior to the classical steepest descent method and has a potential to significantly enhance the computational efficiency and robustness of the training process.

A new conjugate gradient method for acceleration of gradient descent algorithms

University Ferhat Abbas Setif 1, Setif, 19000 and University Center of Tamanrasset

Laboratory Informatics and Mathematics (LiM)

Moroccan Journal of Pure and Applied Analysis

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"A new conjugate gradient method for acceleration of gradient descent algorithms"}

An accelerated of the steepest descent method for solving unconstrained optimization problems is presented. which propose a fundamentally different conjugate...

A new conjugate gradient method for acceleration of gradient descent algorithms

Publié en ligne: 22 nov. 2020

Pages: 1 - 11

Reçu: 05 juil. 2020

Accepté: 12 oct. 2020

DOI: https://doi.org/10.2478/mjpaa-2021-0001

Mots clés
Unconstrained optimization, Conjugate gradient method, Line search, Global convergence

© 2020 Noureddine Rahali et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A new conjugate gradient method for acceleration of gradient descent algorithms

Publié en ligne: 22 nov. 2020

Pages: 1 - 11

Reçu: 05 juil. 2020

Accepté: 12 oct. 2020

DOI: https://doi.org/10.2478/mjpaa-2021-0001

Mots clésUnconstrained optimization, Conjugate gradient method, Line search, Global convergence

© 2020 Noureddine Rahali et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
Unconstrained optimization, Conjugate gradient method, Line search, Global convergence