AN ACCELERATED METHOD OF GRADIENT DESCENT

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Authors

  • Hoa Tat Thang (Corresponding Author) Faculty of Information Technology, Military Technical Academy

Keywords:

Gradient descent; Machine learning; Learning rate; Point initialization; Function loss.

Abstract

Optimization problem is the problem of finding the best solution in best solutions. Optimization has many applications in deep learning real life such as classification problems, image recognition, problems to maximize revenue or reduce costs, production time vv. The gradient descent method usually used to find the optimal solution of a problem quickly. In this report, the author uses a new method to quickly find reasonable learning rate based on the idea of ​​flow control and anti-congestion principle in telecommunication networks to speed up the ability convergence of the problem compared to the conventional gradient descent method.

Published

03-08-2020

How to Cite

Thắng. “AN ACCELERATED METHOD OF GRADIENT DESCENT”. Journal of Military Science and Technology, no. 68, Aug. 2020, pp. 186-93, https://en.jmst.info/index.php/jmst/article/view/169.

Issue

Section

Research Articles