Research Area: Supervised and Unsupervised Learning Methods

Besides our strong interest in machine learning methods that are suited for the application to the real world, we are also investigating more fundamental questions and basic methods of machine learning. Here are some examples:

  • Rprop - a fast and robust learning scheme for supervised learning
  • a new sampling approach for mixture training
  • function approximation schemes

See also our publications page for further information.