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Committee Date Time Place Paper Title / Authors Abstract Paper #
NLP 2008-03-28
11:40		 Hyogo   A Note on Expansion and Contraction of Categories in Fuzzy ARTMAP
Takeshi Kamio (Hiroshima City Univ.), Kunihiko Mitsubori (Takushoku Univ.), Chang-Jun Ahn, Hisato Fujisaka, Kazuhisa Haeiwa (Hiroshima City Univ.) NLP2007-171		 Fuzzy ARTMAP (FAM) is a supervised learning system. FAM segments the input space with categories which are defined by hy... [more] NLP2007-171
pp.25-30
NC, MBE
(Joint)		 2008-03-14
15:50		 Tokyo Tamagawa Univ A Supervised Learning Method Based on Adaptive Resonance Theory Considering Task Complexity
Yusuke Takenaka, Takeshi Kamio, Hisato Fujisaka, Kazuhisa Haeiwa (Hiroshima City Univ.) NC2007-199		 Fuzzy ARTMAP (FAM) is a supervised learning system based on the adaptive resonance theory (ART). If FAM learns samples w... [more] NC2007-199
pp.513-518
NLP 2007-03-06
10:55		 Miyagi   ARTMAP with Explicit and Implicit Weights
Kenji Mori, Takeshi Kamio, Hisato Fujisaka, Kazuhisa Haeiwa (Hirosima City Univ.) 		ARTMAP is a supervised learning system that consists of the adaptive resonance theory neural networks (ART). Since ARTMA... [more] NLP2006-158
pp.21-26
NLP 2006-03-21
11:15		 Tokyo Hosei Univ.(Ichigaya Campus) Improvement of Fuzzy ARTMAP by Controlling Match Tracking
Kentaro Nomura, Takeshi Kamio, Hisato Fujisaka, Kazuhisa Haeiwa (Hiroshima City Univ.) 		Adaptive resonance theory neural network (ART) is an unsupervised learning system that can generate and grow the recogni... [more] NLP2005-154
pp.19-24
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