Analysis of On-Line Learning when a Moving Teacher Goes around a True Teacher
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- Miyoshi Seiji
- Department of Electronic Engineering, Kobe City College of Technology
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- Okada Masato
- Division of Transdisciplinary Sciences, Graduate School of Frontier Sciences, The University of Tokyo RIKEN Brain Science Institute JST PRESTO
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Abstract
In the framework of on-line learning, a learning machine might move around a teacher due to the differences in structures or output functions between the teacher and the learning machine or due to noises. The generalization performance of a new student supervised by a moving machine has been analyzed. A model composed of a fixed true teacher, a moving teacher and a student that are all linear perceptrons with noises has been treated analytically using statistical mechanics. It has been proven that the generalization errors of a student can be smaller than that of a moving teacher, even if the student only uses examples from the moving teacher.
Journal
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- Journal of the Physical Society of Japan
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Journal of the Physical Society of Japan 75 (2), 024003-, 2006
THE PHYSICAL SOCIETY OF JAPAN
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Details 詳細情報について
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- CRID
- 1390001204189882752
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- NII Article ID
- 210000105994
- 110004086865
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- NII Book ID
- AA00704814
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- BIBCODE
- 2006JPSJ...75b4003M
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- ISSN
- 13474073
- 00319015
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- NDL BIB ID
- 7813093
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed