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TNN
1998
146views more  TNN 1998»
14 years 9 months ago
Fuzzy lattice neural network (FLNN): a hybrid model for learning
— This paper proposes two hierarchical schemes for learning, one for clustering and the other for classification problems. Both schemes can be implemented on a fuzzy lattice neu...
Vassilios Petridis, Vassilis G. Kaburlasos
NPL
2006
137views more  NPL 2006»
14 years 9 months ago
Minimal Structure of Self-Organizing HCMAC Neural Network Classifier
The authors previously proposed a self-organizing Hierarchical Cerebellar Model Articulation Controller (HCMAC) neural network containing a hierarchical GCMAC neural network and a ...
Chih-Ming Chen, Yung-Feng Lu, Chin-Ming Hong
NIPS
1992
14 years 10 months ago
Explanation-Based Neural Network Learning for Robot Control
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
Tom M. Mitchell, Sebastian Thrun
IJCNN
2007
IEEE
15 years 3 months ago
Parallel Learning of Large Fuzzy Cognitive Maps
— Fuzzy Cognitive Maps (FCMs) are a class of discrete-time Artificial Neural Networks that are used to model dynamic systems. A recently introduced supervised learning method, wh...
Wojciech Stach, Lukasz A. Kurgan, Witold Pedrycz
ML
2010
ACM
175views Machine Learning» more  ML 2010»
14 years 4 months ago
Concept learning in description logics using refinement operators
With the advent of the Semantic Web, description logics have become one of the most prominent paradigms for knowledge representation and reasoning. Progress in research and applica...
Jens Lehmann, Pascal Hitzler