A new two-step inertial algorithm for solving convex bilevel optimization problems with application in data classification problems

In this paper, we propose a new accelerated algorithm for solving convex bilevel optimization problems using some fixed point and two-step inertial techniques. Our focus is on analyzing the convergence behavior of the proposed algorithm. We establish a strong convergence theorem for our algorithm un...

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Bibliographic Details
Published inAIMS mathematics Vol. 9; no. 4; pp. 8476 - 8496
Main Authors Sae-jia, Puntita, Suantai, Suthep
Format Journal Article
LanguageEnglish
Published AIMS Press 01.01.2024
Subjects
accelerated algorithm
convex bilevel optimization problem
data classification
noncommunicable diseases
two-step inertial algorithm
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Summary:In this paper, we propose a new accelerated algorithm for solving convex bilevel optimization problems using some fixed point and two-step inertial techniques. Our focus is on analyzing the convergence behavior of the proposed algorithm. We establish a strong convergence theorem for our algorithm under some control conditions. To demonstrate the effectiveness of our algorithm, we utilize it as a machine learning algorithm to solve data classification problems of some noncommunicable diseases, and compare its efficacy with BiG-SAM and iBiG-SAM.
ISSN:2473-6988
2473-6988
DOI:10.3934/math.2024412