Statistical Mechanical Analysis of Simultaneous Perturbation Learning
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概要
- 論文の詳細を見る
We show that simultaneous perturbation can be used as an algorithm for on-line learning, and we report our theoretical investigation on generalization performance obtained with a statistical mechanical method. Asymptotic behavior of generalization error using this algorithm is on the order of t to the minus one-third power, where t is the learning time or the number of learning examples. This order is the same as that using well-known perceptron learning.
- （社）電子情報通信学会の論文
- 2009-07-01
著者
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Miyoshi Seiji
Department Of Electrical And Electronic Engineering Faculty Of Engineering Science Kansai University
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HIKAWA Hiroomi
Department of Computer Science and Intelligent Systems, Oita University
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Hikawa Hiroomi
Department Of Electrical And Electronic Engineering Faculty Of Engineering Science Kansai University
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Maeda Yutaka
Department Of Applied Biological Science Tokyo University Of Science
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Maeda Yutaka
Department Of Electrical And Electronic Engineering Faculty Of Engineering Science Kansai University
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Miyoshi Seiji
Fac. Of Engineering Sci. Kansai Univ.
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