Presentation | 2006-05-18 New Approaches to the Relation between Computational Learning and Machine Learning Akihiro YAMAMOTO, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | The relation between Logic and Machine Learning is investigated for a long time. The major approach to the goal is using logic in learning: using syntax of logic for representation of data and knowledge, applying automated theorem proving to keeping consistency of hypotheses to given examples, and guaranteeing the appropriateness of learning with semantics of logic. Recently researches on new approaches to the relation have appeared. In this survey we introduce such new researches, in particular, relation between logic and parameter estimation, relation between logic and data-mining, application of logic to the Support Vector Machine, and Machine Learning in Computational Algebra. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Computational Logic / Machine Learning / Inductive Logic Programming |
Paper # | AI2006-7 |
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Conference Information | |
Committee | AI |
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Conference Date | 2006/5/11(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | New Approaches to the Relation between Computational Learning and Machine Learning |
Sub Title (in English) | |
Keyword(1) | Computational Logic |
Keyword(2) | Machine Learning |
Keyword(3) | Inductive Logic Programming |
1st Author's Name | Akihiro YAMAMOTO |
1st Author's Affiliation | Graduate School of Informatics, Kyoto University() |
Date | 2006-05-18 |
Paper # | AI2006-7 |
Volume (vol) | vol.106 |
Number (no) | 38 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |