With the technical development of multi-electrode arrays, the monitoring of many individual neurons has become feasible. However, for practical use of those arrays as bidirectional...
Andreas Herzog, Karsten Kube, Bernd Michaelis, Ana...
Incomplete data is a common drawback that machine learning techniques need to deal with when solving real-life classification tasks. One of the most popular procedures for solving ...
Computational neuroscience is an appealing interdisciplinary domain, at the interface between biology and computer science. It aims at understanding the experimental data obtained...
Many tools for data mining are complex and require skills and experience to be used successfully. Therefore, data mining is often considered an art as much as science. This paper p...
The analysis of spectral data constitutes new challenges for machine learning algorithms due to the functional nature of the data. Special attention is paid to the metric used in t...
Petra Schneider, Frank-Michael Schleif, Thomas Vil...
A new approach for faithful relevance rating of attributes is proposed, enabling class-specific discriminatory data space transformations. The method is based on the adaptation of ...
Marc Strickert, Frank-Michael Schleif, Thomas Vill...
The evaluation of a standard Gaussian process regression model takes time linear in the number of training data points. In this paper, the models are approximated in the feature sp...