| Project/Area Number |
20700130
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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 | Tokyo Institute of Technology |
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Principal Investigator |
SAKUMA Jun Tokyo Institute of Technology, 大学院・システム情報工学研究科, 准教授 (90376963)
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| Project Period (FY) |
2008 – 2009
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| Project Status |
Completed (Fiscal Year 2009)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2009: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2008: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
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| Keywords | プライバシ / データマイニング / モデル選択 / 属性選択 / 単純ベイズ / サポートベクターマシン / プライバシー / セキュリティ / 組み合わせ最適化 / 強化学習 / メタヒューリスティック / 遺伝的アルゴリズム / 局所探索 |
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| Research Abstract |
In this research project, learning and optimization from privately distributed data sources have been studied. Specifically, algorithm design, security, and performance evaluation has been considered. The traveling salesman problem, reinforcement learning, and pre/post-processing of classification tasks have been focused as target algorithms. In order to securely perform these algorithms with taking privately distributed information, protocol are specifically designed for each algorithm by making use of homomorphic public-key cryptosystem. Furthermore, we proved the security of these protocols. The assessment of the computational efficiency has been performed experimentally.
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