A parallel inertial S-iteration forward-backward algorithm for regression and classification problems

© 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 di...

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Bibliographic Details
Main Authors: Limpapat Bussaban, Suthep Suantai, Attapol Kaewkhao
Format: Journal
Published: 2020
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85082410307&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/70734
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Institution: Chiang Mai University
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Summary:© 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.