| Co-Investigator(Kenkyū-buntansha) |
篠原 歩 東北大学, 情報科学研究科, 教授 (00226151)
正代 隆義 九州国際大学, 国際関係学部, 教授 (50226304)
畑埜 晃平 九州大学, 附属図書館, 准教授 (60404026)
吉仲 亮 京都大学, 情報学研究科, 助教 (80466424)
内沢 啓 山形大学, 理工学研究科, 准教授 (90510248)
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| Budget Amount *help |
¥31,200,000 (Direct Cost: ¥24,000,000、Indirect Cost: ¥7,200,000)
Fiscal Year 2016: ¥5,980,000 (Direct Cost: ¥4,600,000、Indirect Cost: ¥1,380,000)
Fiscal Year 2015: ¥6,370,000 (Direct Cost: ¥4,900,000、Indirect Cost: ¥1,470,000)
Fiscal Year 2014: ¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000)
Fiscal Year 2013: ¥5,460,000 (Direct Cost: ¥4,200,000、Indirect Cost: ¥1,260,000)
Fiscal Year 2012: ¥6,890,000 (Direct Cost: ¥5,300,000、Indirect Cost: ¥1,590,000)
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| Outline of Final Research Achievements |
We made considerable achievements in bringing new insights into "computation", through the analysis of the complexity of learning problems. In the analysis of online prediction, we partially solved an important open problem, stating the equivalence between the complexity of online prediction and that of optimization. In the analysis of the complexity of hypothesis representation, we proposed a few decision problems defined on the discrete dynamical system, which is a generalization of recurrent neural networks. Our analysis suggests that the decision problems belong to an intermediate layer of the class of NP. In the analysis of learning grammars, we employs a breakthrough technique called the distributional learning and obtained many positive results in learning formal (graph) grammars. The distributional learning is a resume of designing learning algorithms by focusing on the relation of substrings/subgraphs and the structures surrounding them.
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