Data analysis for high-dimensional data with discrete structures and its applications
| Project/Area Number |
22700147
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Intelligent informatics
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| Research Institution | Osaka University |
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Principal Investigator |
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2012: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2011: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2010: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
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| Keywords | 機械学習 / データマイニング / 組合せ最適化 / 劣モジュラ関数最適化 / 離散凸構造 / 特徴選択 / 情報基盤 / アルゴリズム / バイオインフォマティクス / 離散構造 / 情報基礎 |
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| Research Abstract |
The main goal of this research is to develop methodologies for efficient searches of solutions with global optimality or for incorporating discrete structures as prior knowledge in combinatorial analyses with high-dimensional data. Moreover, we aim at its evaluation of the usefulness in applications where combinatorial computation plays a central role. We developed some fundamental algorithms to calculate global/approximate optimal solutions in problems that are known to be difficult to solve(such as, NP-hard problems). Also, we studied a framework for the calculation where we can incorporate such discrete structures as prior knowledge into data analysis for efficient and accurate combinatorial calculation. Furthermore, we applied the developed methods to several applications and investigate the usefulness of the framework.
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Report
(4 results)
Research Products
(67 results)
