116 search results - page 4 / 24 » Neural Networks Training with Optimal Bounded Ellipsoid Algo... |
GECCO
2004
Springer
14 years 26 days ago
2004
Springer
Abstract. Training neural networks is a complex task of great importance in the supervised learning field of research. In this work we tackle this problem with five algorithms, a...
TNN
2010
13 years 2 months ago
2010
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
ML
2007
ACM
13 years 7 months ago
2007
ACM
We propose a general-purpose stochastic optimization algorithm, the so-called annealing stochastic approximation Monte Carlo (ASAMC) algorithm, for neural network training. ASAMC c...
CEC
2007
IEEE
14 years 1 months ago
2007
IEEE
— In this paper, a neural network approach is presented to expand the Pareto-optimal front for multiobjective optimization problems. The network is trained using results obtained...
GECCO
1999
Springer
13 years 11 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...