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NN
2006
Springer
146views Neural Networks» more  NN 2006»
15 years 3 months ago
Comparison of relevance learning vector quantization with other metric adaptive classification methods
The paper deals with the concept of relevance learning in learning vector quantization and classification. Recent machine learning approaches with the ability of metric adaptation...
Thomas Villmann, Frank-Michael Schleif, Barbara Ha...
IJCAI
1989
15 years 4 months ago
Integrating Knowledge-Based System and Neural Network Techniques for Robotic Skill Acquisition
This paper describes an approach to robotic control that is patterned after models of human skill acquisition. The intent is to develop robots capable of learning how to accomplis...
David Handelman, Stephen Lane, Jack Gelfand
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
16 years 3 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
IJCNN
2006
IEEE
15 years 9 months ago
Ensemble Techniques for Avoiding Poor Performance in Evolved Neural Networks
— The idea of using evolutionary techniques to optimize the performance of neural networks is now widely used, but some approaches have been found to result in the evolution of r...
John A. Bullinaria
CEC
2007
IEEE
15 years 7 months ago
Comparison of a multi-layered artificial immune system with a kohonen network
We present a novel multi-layered unsupervised learning artifical immune system (MARIA). We have employed vector quantisation to augment MARIA (and Kohonen Networks) to allow for a ...
Thomas Knight, Jonathan Timmis