| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2020: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2019: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Outline of Final Research Achievements |
In this study, we consider primal-dual sparse optimization models that have sparse primal and dual solutions for large-scale optimization problems in data analysis, machine learning, and financial engineering. We develop efficient solution methods for them. We presented two-type of formulations of the primal-dual sparse models, and proposed solution methods based on the method of multipliers and the implicit programming approach. Furthermore, we applied our findings in this study to multi-objective optimization, the Levenberg-Marquardt method, and multi-valued support vector machines.
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