A Novel Inertial Viscosity Algorithm for Bilevel Optimization Problems Applied to Classification Problems

Kobkoon Janngam, Suthep Suantai, Yeol Je Cho, Attapol Kaewkhao and Rattanakorn Wattanataweekul ()
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Kobkoon Janngam: Graduate Ph.D. Degree Program in Mathematics, Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
Suthep Suantai: Research Center in Optimization and Computational Intelligence for Big Data Prediction, Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
Yeol Je Cho: Department of Mathematics Education, Gyeogsang National University, Jinju 52828, Republic of Korea
Attapol Kaewkhao: Research Center in Optimization and Computational Intelligence for Big Data Prediction, Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
Rattanakorn Wattanataweekul: Department of Mathematics, Statistics and Computer, Faculty of Science, Ubon Ratchathani University, Ubon Ratchathani 34190, Thailand

Mathematics, 2023, vol. 11, issue 14, 1-15

Abstract: Fixed-point theory plays many important roles in real-world problems, such as image processing, classification problem, etc. This paper introduces and analyzes a new, accelerated common-fixed-point algorithm using the viscosity approximation method and then employs it to solve convex bilevel optimization problems. The proposed method was applied to data classification with the Diabetes, Heart Disease UCI and Iris datasets. According to the data classification experiment results, the proposed algorithm outperformed the others in the literature.

Keywords: classification problems; convex bilevel optimization; forward–backward algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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