Shun-Ichi Amari, Naotake Fujita, Shigeru Shinomoto  Home/Search
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Abstract: In learning from examples, the generalization error (t) is the average probability that an incorrect decision is made by a machine trained by t examples. The generalization error decreases as t increases, and the curve (t) is called a learning curve. The present paper uses the Bayesian approach to show that, under the random phase approximation (annealed approximation), learning curves are classified into four asymptotic types depending on situations. When a machine is deterministic with... (Update)
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.... been some efforts to use statistical mechanics and other approaches to understand feedforward neural networks and learning from examples [1,12]. Although considerable efforts have been devoted to the development of various ANN learning paradigms, improvement of the existing...
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BibTeX entry: (Update)
S. Amari, N. Fujita, and S. Shinomoto. Four types of learning curves. Neural Comput., 4:605--618, 1992. http://citeseer.ist.psu.edu/amari91four.html More
@article{ shunichi92four,
author = "Amari, {Shun-ichi} and Fujita, N. and Shinomoto, S.",
title = "Four Types of Learning Curves",
journal = "Neural Computation",
volume = "4",
number = "4",
pages = "605--618",
year = "1992",
url = "citeseer.ist.psu.edu/amari91four.html" }
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