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dc.contributor.authorLimpapat Bussabanen_US
dc.contributor.authorSuthep Suantaien_US
dc.contributor.authorAttapol Kaewkhaoen_US
dc.description.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.en_US
dc.titleA parallel inertial S-iteration forward-backward algorithm for regression and classification problemsen_US
article.title.sourcetitleCarpathian Journal of Mathematicsen_US
article.volume36en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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