Presentation | 2002/5/13 A Note on Computational Learning and Information Compression Makoto NAKAZAWA, Toshiyasu MATSUSHIMA, Shigeichi HIRASAWA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Recently, grammar based codes are researched in the area of lossless source coding. But, it is not clear which formal grammars is appropriate in Chomsky hierarchy for information compression. In this paper, we consider grammar based codes as the process of deriving automata based on machine learning and it is a purpose to clarify what influence the class of grammars or languages gives the encoding in the view of machine learning. I will show that Bayes algorithm outputs the shortest hypothesis in the class and some class has feasible complexity in order to ouput optimal hypothesis based on computational learning theory. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | formal grammars / lossless compression / computational learning / Bayes algorithm / time complexity |
Paper # | IT2002-7 |
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Committee | IT |
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Conference Date | 2002/5/13(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Information Theory (IT) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | A Note on Computational Learning and Information Compression |
Sub Title (in English) | |
Keyword(1) | formal grammars |
Keyword(2) | lossless compression |
Keyword(3) | computational learning |
Keyword(4) | Bayes algorithm |
Keyword(5) | time complexity |
1st Author's Name | Makoto NAKAZAWA |
1st Author's Affiliation | Media Network Center, Waseda University() |
2nd Author's Name | Toshiyasu MATSUSHIMA |
2nd Author's Affiliation | School of Science and Engineering, Waseda University |
3rd Author's Name | Shigeichi HIRASAWA |
3rd Author's Affiliation | School of Science and Engineering, Waseda University |
Date | 2002/5/13 |
Paper # | IT2002-7 |
Volume (vol) | vol.102 |
Number (no) | 66 |
Page | pp.pp.- |
#Pages | 6 |
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