Designing practical algorithms for learning formal languages based on distribution of strings in contexts
| Project/Area Number |
23700156
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Intelligent informatics
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| Research Institution | Kyoto University |
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Principal Investigator |
YOSHINAKA Ryo 京都大学, 情報学研究科, 助教 (80466424)
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| Project Period (FY) |
2011 – 2013
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2012: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2011: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Keywords | 文法推論 / 文脈自由言語 / 弱文脈依存言語 / 分布学習 / 計算論的学習 / 計算論的学習理論 / PAC学習 / 国際研究者交流（イギリス） / 非準線形言語 |
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| Research Abstract |
Recently the approaches generically called "distributional learning" have been making a great success in the learning of context-free languages. This research project revealed the exact mathematical symmetry of the two types of distributional learning approaches. Based on this observation, we gave a uniform view of the existing distributional learning algorithms and designed an algorithm which integrates existing distributional learning algorithms in it. The obtained algorithm is stronger than other distributional learners for context-free languages. Moreover, we showed that the techniques can be applied to different grammar formalisms that are more powerful than context-free grammars in a uniform way. We also proposed an algorithm that learns certain context-free languages from positive examples only with high probability and accuracy.
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Report
(4 results)
Research Products
(17 results)
