| Budget Amount *help |
¥15,990,000 (Direct Cost: ¥12,300,000、Indirect Cost: ¥3,690,000)
Fiscal Year 2017: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2016: ¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
Fiscal Year 2015: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2014: ¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
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| Outline of Final Research Achievements |
In this study, we developed several machine learning algorithms based on discrete convexity such as submodularity. In particular, we developed efficient learning algorithm with structured sparsity, which is formulated with continuous relaxations of submodular functions. We applied those to problems in several engineering fields, and confirmed the proposed methods effectiveness in those problems.
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