State-of-the-art pattern recognition methods have difficulty dealing with problems where the dimension of the output space is large. In this article, we propose a new framework ba...
— This paper shows the advantage of using neural network modularity over conventional learning schemes to approximate complex functions. Indeed, it is difficult for artificial ...
The design of an autonomous navigation system for mobile robots can be a tough task. Noisy sensors, unstructured environments and unpredictability are among the problems which mus...
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba...
A novel multistage feedforward network is proposed for efficient solving of difficult classification tasks. The standard Radial Basis Functions (RBF) architecture is modified in or...
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...