950 search results - page 31 / 190 » Training a Quantum Neural Network |
ICANN
2001
Springer
14 years 5 days ago
2001
Springer
Support vector machines have gotten wide acceptance for their high generalization ability for real world applications. But the major drawback is slow training for classification p...
GECCO
1999
Springer
13 years 12 months ago
1999
Springer
In this work MagnetoEncephaloGram (MEG) recordings of epileptic patients were analyzed using a hybrid neural networks training algorithm. This algorithm combines genetic algorithm...
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Neural networks learn by adjusting numeric values called weights and thresholds. A weight specifies how strong of a connection exists between two neurons. A threshold is a value,...
ANNPR
2006
Springer
13 years 11 months ago
2006
Springer
We discuss incremental training of support vector machines in which we approximate the regions, where support vector candidates exist, by truncated hypercones. We generate the trun...
ICDAR
2003
IEEE
14 years 29 days ago
2003
IEEE
Neural networks are a powerful technology for classification of visual inputs arising from documents. However, there is a confusing plethora of different neural network methods th...