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» Fuzzy-Kernel Learning Vector Quantization
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NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 10 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin
ICONIP
2008
14 years 6 days ago
A Vector Quantization Approach for Life-Long Learning of Categories
We present a category learning vector quantization (cLVQ) approach for incremental and life-long learning of multiple visual categories where we focus on approaching the stability-...
Stephan Kirstein, Heiko Wersing, Horst-Michael Gro...
WSOM
2009
Springer
14 years 5 months ago
Incremental Figure-Ground Segmentation Using Localized Adaptive Metrics in LVQ
Vector quantization methods are confronted with a model selection problem, namely the number of prototypical feature representatives to model each class. In this paper we present a...
Alexander Denecke, Heiko Wersing, Jochen J. Steil,...
PR
2006
120views more  PR 2006»
13 years 10 months ago
Alternative learning vector quantization
In this paper, we discuss the influence of feature vectors contributions at each learning time t on a sequential-type competitive learning algorithm. We then give a learning rate ...
Kuo-Lung Wu, Miin-Shen Yang
NN
2006
Springer
146views Neural Networks» more  NN 2006»
13 years 10 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...