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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
IBISML |
2019-03-05 14:00 |
Tokyo |
RIKEN AIP |
Expressive power of skip connection and network architecture Jumpei Nagase, Tetsuya Ishiwata (Shibaura Inst. of Tech.) IBISML2018-106 |
Model design is one of research topics in deep learning. Proposing a better model has been extensively studied, but ther... [more] |
IBISML2018-106 pp.9-15 |
ICM, LOIS |
2019-01-24 14:00 |
Kagoshima |
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Analysis of behaviors of audience in presentations (Third report) Eiji Watanabe (Konan Univ.), Takashi Ozeki (Fukuyama Univ.), Takeshi Kohama (Kindai Univ.) ICM2018-39 LOIS2018-45 |
In presentations using slides, lecturers have to estimate the interests of the audience based on the behaviors of the au... [more] |
ICM2018-39 LOIS2018-45 pp.21-26 |
NC, MBE (Joint) |
2010-03-11 14:10 |
Tokyo |
Tamagawa University |
Neural Network Model for Sequential Learning of Time-series can Learn the Stimulus Equivalence Jun Uchida, Hiroyuki Okada (Tamagawa Univ.) NC2009-168 |
If human being is trained to choose the stimulus (B) corresponding to other one (A), he or she can choose A for the pres... [more] |
NC2009-168 pp.473-478 |
NLP |
2009-02-28 16:35 |
Kanagawa |
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Response Properties of Chaotic Neural Network Model to Memory Pattern Flagments Toshiyuki Hamada, Jousuke Kuroiwa, Hisakazu Ogura, Tomohiro Odaka, Haruhiko Shirai (Univ of Fukui) NLP2008-149 |
In this paper, we investigate response properties to memory pattern fragments
in chaotic wandering states among three ... [more] |
NLP2008-149 pp.101-106 |
NLP |
2009-02-28 16:55 |
Kanagawa |
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Delay Feedback Control to Chaotic Neural Network Model Kouta Teramoto, Jousuke Kuroiwa, Hisakazu Ogura, Tomohiro Odaka, Haruhiko Shirai (Univ of Fukui) NLP2008-150 |
In this paper, we investigate a delay feedback control to chaotic wandering states in chaotic neural network model. In m... [more] |
NLP2008-150 pp.107-111 |
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