Statistical Mechanics of Time-Domain Ensemble Learning(General)
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概要
- 論文の詳細を見る
Conventional ensemble learning combines students in the space domain. On the other hand, in this paper, we combine students in the time domain and call it time-domain ensemble learning. We analyze the generalization performance of time-domain ensemble learning in the framework of on-line learning using a statistical mechanical method. We use a model in which both the teacher and the student are linear perceptrons with noises. Time-domain ensemble learning is twice as effective as conventional space-domain ensemble learning.
- 社団法人日本物理学会の論文
- 2006-08-15
著者
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OKADA Masato
Division of Protein Metabolism, Institute for Protein Research, Osaka University
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Miyoshi Seiji
Department Of Electronic Engineering Kobe City College Of Technology
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Miyoshi Seiji
Department Of Electrical And Electronic Engineering Faculty Of Engineering Science Kansai University
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OKADA MASATO
Graduate School of Frontier Sciences, The University of Tokyo
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UEZU Tatsuya
Graduate School of Humanities and Sciences, Nara Women's University
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Uezu Tatsuya
Graduate School Of Human Culture Nara Women's University
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Miyoshi Seiji
Kobe City College Of Technology
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OKADA Masato
University of Tokyo
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Okada Masato
Division Of Transdisciplinary Of Sciences Graduate School Of Frontier Sciences The University Of Tok
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Okada Masato
Division Of Protein Metabolism Institute For Protein Research Osaka University
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Uezu Tatsuya
Nara Women's Univ. Nara
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OKADA Masato
Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute:"Intelligent Cooperation and Control", PRESTO, JST, co RIKEN BSI:Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, the University of To
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Okada Masato
Division of Allergy and Rheumatology, St. Luke's International Hospital, Japan
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OKADA Masato
Division of Allergy and Rheumatology, St. Luke's International Hospital
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