2016 Fiscal Year Final Research Report
Hardware-friendly machine learning with integer-parameter regularized learning based on discrete convexity
| Project/Area Number |
25540102
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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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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| Co-Investigator(Renkei-kenkyūsha) |
NAGANO Kiyohito 群馬大学, 社会情報学部 (20515176)
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| Project Period (FY) |
2013-04-01 – 2017-03-31
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| Keywords | 機械学習 |
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| Outline of Final Research Achievements |
We have made a study regularized learning algorithms over integer parameters, and compared several different approaches for that. However, currently, theoretical problems that we did not expected have been revealed, and the computational costs for carrying out those with computers have been revealed. Based on these considerations, as another option, we have considered an approach where learning is performed with structural information among parameters in data. And, we confirmed it could be useful for the purpose of this research project.
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| Free Research Field |
機械学習
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