ESANN 2004: Bruges, Belgium

Learning I

Theory and applications of neural maps

Bayesian learning and Markov processes

Sof-computing techniques for time series forecasting

Learning II

Indepedent compent analysis and non-linear projection

Industrial applications of neural networks

Neural methods for non-standard data

Learning III

Hardware systems for neural devices

Support vector machines

Neural networks for data mining

Learning IV

maintained by Schloss Dagstuhl LZI at University of Trier