ESANN
2003
14 years 2 months ago
2003
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
ESANN
2003
14 years 2 months ago
2003
This paper presents a novel vector quantizer (VQ) design algorithm for a burst error channel (BEC). The algorithm minimizes the average distortion when the BEC is in normal state o...
ESANN
2003
14 years 2 months ago
2003
A novel feature selection methodology is proposed with the concept of mutual information. The proposed methodology effectively circumvents two major problems in feature selection ...
ESANN
2003
14 years 2 months ago
2003
Abstract. We focus on covariance criteria for finding a suitable subspace for regression in a reproducing kernel Hilbert space: kernel principal component analysis, kernel partial...
ESANN
2003
14 years 2 months ago
2003
Training an ensemble of networks is an interesting way to improve the performance with respect to a single network. However there are several method to construct the ensemble and t...
ESANN
2003
14 years 2 months ago
2003
In this paper we propose a new algorithm for rule extraction from a trained Multilayer Feedforward network. The algorithm is based on an interval arithmetic network inversion for p...
ESANN
2003
14 years 2 months ago
2003
Abstract. This paper considers the general problem of function estimation with a modular approach of neural computing. We propose to use functionally independent subnetworks to lea...
ESANN
2003
14 years 2 months ago
2003
Abstract. Application of neural networks for real world object recognition suffers from the need to acquire large quantities of labelled image data. We propose a solution that acq...
ESANN
2003
14 years 2 months ago
2003
In this tutorial paper about mathematical aspects of neural networks, we will focus on two directions: on the one hand, we will motivate standard mathematical questions and well st...
ESANN
2003
14 years 2 months ago
2003
In this paper, we propose a new network growth model and its learning algorithm to more precisely model such a real-world growing network as the Web. Unlike the conventional model...