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Learning finite functions by neural networks : Evaluation of Pentago positions by convolutional neural networks (Algebras, logics, languages and related areas)
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- Jimbo, Shuji
- Graduate School of Natural Science and Technology, Okayama University
Bibliographic Information
- Other Title
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- Learning finite functions by neural networks : Evaluation of Pentago positions by convolutional neural networks
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Description
A convolution neural network (CNN) is a useful tool that approximates a finite function. It is used as a solver for various problems in the real world. In this paper, results of experiments on training variations of a small CNN used for image recognition for evaluating Pentago positions are mainly reported. The author hopes that the results are used in discussion of applicability of deep neural networks to researches in theoretical computer science.
Journal
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- RIMS Kokyuroku
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RIMS Kokyuroku 2096 25-31, 2018-12
京都大学数理解析研究所
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Keywords
Details 詳細情報について
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- CRID
- 1050566774764162816
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- NII Article ID
- 120006861343
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- NII Book ID
- AN00061013
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- ISSN
- 18802818
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- HANDLE
- 2433/251730
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- NDL BIB ID
- 029623906
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- Text Lang
- en
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- Article Type
- departmental bulletin paper
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- Data Source
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- IRDB
- NDL Search
- CiNii Articles