Abstract— We present a grammar-based genetic programming framework for the solving the timetabling problem via the evolution of constructive heuristics. The grammar used for prod...
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...
Extensive labeled data for image annotation systems, which learn to assign class labels to image regions, is difficult to obtain. We explore a hybrid model framework for utilizing...
Spatial filtering is a widely used dimension reduction method in electroencephalogram based brain-computer interface systems. In this paper a new algorithm is proposed, which learn...
We develop a new approach to learning phrase translations from parallel corpora, and show that it performs with very high coverage and accuracy in choosing French translations of ...