In this paper we show that rotational invariance can be improved in a neural network based EIT reconstruction approach by a suitably chosen permutation of the input data. The inpu...
The paper describes our first experiments on Reinforcement Learning to steer a real robot car. The applied method, Neural Fitted Q Iteration (NFQ) is purely data-driven based on ...
Martin Riedmiller, Michael Montemerlo, Hendrik Dah...
Clustering algorithms such as k-means, the self-organizing map (SOM), or Neural Gas (NG) constitute popular tools for automated information analysis. Since data sets are becoming l...
Combining machine learning models is a means of improving overall accuracy.Various algorithms have been proposed to create aggregate models from other models, and two popular examp...
This paper proposes an on-line error detecting method for a manually annotated corpus using min-max modular (M3 ) neural networks. The basic idea of the method is to use guaranteed...