This paper is devoted to the analysis of network approximation in the framework of approximation and regularization theory. It is shown that training neural networks and similar n...
Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...
Actor-critic algorithms for reinforcement learning are achieving renewed popularity due to their good convergence properties in situations where other approaches often fail (e.g.,...
Combining the ant colony algorithm (ACA) and the neural network (NN), the present paper puts forward an approach to traffic volume forecasting based on the ant colony neural netwo...
: The main contribution of this report is the development of an integer recurrent artificial neural network (IRANN) for classification of feature vectors. The network consists both...