Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems

Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. It utilizes the concept of classical gradient descent method with modification on the gradient selection. SGD uses random or batch data sets to compute gradient in solvin...

Popoln opis

Shranjeno v:
Bibliografske podrobnosti
Main Authors: Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong
Format: Article
Jezik:English
Izdano: Persatuan Sains Matematik Malaysia 2023
Online dostop:http://psasir.upm.edu.my/id/eprint/110372/1/document%20%284%29.pdf
Oznake: Označite
Brez oznak, prvi označite!