4 search results - page 1 / 1 » Learning Vector Quantization: generalization ability and dyn... |
DAGSTUHL
2007
13 years 6 months ago
2007
IJON
2006
13 years 4 months ago
2006
Winner-Takes-All (WTA) prescriptions for Learning Vector Quantization (LVQ) are studied in the framework of a model situation: Two competing prototype vectors are updated accordin...
IJON
2008
13 years 4 months ago
2008
Various alternatives have been developed to improve the Winner-Takes-All (WTA) mechanism in vector quantization, including the Neural Gas (NG). However, the behavior of these algo...
ESANN
2006
13 years 6 months ago
2006
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...