Learning finite functions by neural networks : Evaluation of Pentago positions by convolutional neural networks
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- 神保, 秀司
- 岡山大学
書誌事項
- タイトル別名
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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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説明
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.
収録刊行物
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- 数理解析研究所講究録
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数理解析研究所講究録 2096 25-31, 2018-12
京都大学数理解析研究所
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詳細情報 詳細情報について
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- CRID
- 1050566774764162816
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- NII論文ID
- 120006861343
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- NII書誌ID
- AN00061013
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- ISSN
- 18802818
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- HANDLE
- 2433/251730
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- NDL書誌ID
- 029623906
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- 本文言語コード
- en
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- 資料種別
- departmental bulletin paper
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- データソース種別
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- IRDB
- NDLサーチ
- CiNii Articles