Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/70734
Title: A parallel inertial S-iteration forward-backward algorithm for regression and classification problems
Authors: Limpapat Bussaban
Suthep Suantai
Attapol Kaewkhao
Authors: Limpapat Bussaban
Suthep Suantai
Attapol Kaewkhao
Keywords: Mathematics
Issue Date: 1-Jan-2020
Abstract: © 2020, SINUS Association. All rights reserved. In this paper, a novel algorithm, called parallel inertial S-iteration forward-backward algorithm (PISFBA) is proposed for finding a common fixed point of a countable family of nonexpansive mappings and convergence behavior of PISFBA is analyzed and discussed. As applications, we apply PISFBA to estimate the weight connecting the hidden layer and output layer in a regularized extreme learning machine. Finally, the proposed learning algorithm is applied to solve regression and data classification problems.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85082410307&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/70734
ISSN: 18434401
15842851
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.