Presentation | 2003/10/16 Emergence of category-baias based learning learning acceleration in coherent neuralnetworks Toshihiko HAMANO, Akira HIROSE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | By regarding the carrier frequency as an internal state in coherent neural networks, such a function is realizable by a self-organizing mechanism that identical input yields different outputs according to its internal state. In this paper, we analyze the learning acceleration by introducing contextual I/O patterns as a category bias condition. In the result, on the category bias condition including the contextual I/O patterns, there is a steeper learning acceleration than on the non-category bias condition. This result shows the potentiality that, based on this system, a self-organizing informaiton system that has human-like learning function will be realized. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | category bias / acceleration / hierarchy |
Paper # | PRMU2003-115,NC2003-46 |
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Committee | PRMU |
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Conference Date | 2003/10/16(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Emergence of category-baias based learning learning acceleration in coherent neuralnetworks |
Sub Title (in English) | |
Keyword(1) | category bias |
Keyword(2) | acceleration |
Keyword(3) | hierarchy |
1st Author's Name | Toshihiko HAMANO |
1st Author's Affiliation | Department of Frontier Informatics, Graduate School of Frontier Sciences, The University of Tokyo() |
2nd Author's Name | Akira HIROSE |
2nd Author's Affiliation | Department of Frontier Informatics, Graduate School of Frontier Sciences, The University of Tokyo |
Date | 2003/10/16 |
Paper # | PRMU2003-115,NC2003-46 |
Volume (vol) | vol.103 |
Number (no) | 389 |
Page | pp.pp.- |
#Pages | 6 |
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