1     2     3     4     5     6     7     8     9     10     11     12    

B.-J. Jain, P. Geibel, and F. Wysotzki: Combining Recurrent Neural Networks and Support Vector Machines for Structural Pattern Recognition. Neurocomputing, vol. 64, pp. 63-105, 2005. PDF (preliminary version)


P. Geibel and F. Wysotzki: Learning perceptrons and piecewise linear classifiers sensitive to example dependent costs. Applied Intelligence, 21(1):45—56, 2004.

P. Geibel, U. Brefeld, and F. Wysotzki: Perceptron and SVM learning with generalized cost models. Intelligent Data Analysis, 8(5):439 – 455, 2004. PDF (preliminary version)

P. Geibel, B.-J. Jain, and F. Wysotzki: Combining recurrent neural networks and support vector machines for classifying structured data. In KI 2004: Advances in Artificial Intelligence -- 27th Annual German Conference on AI. Springer-Verlag, 2004. PDF

P. Geibel, B.-J. Jain, and F. Wysotzki: SVM learning with the SH inner product. In M. Verleysen (ed.), Proceedings of the 12th European Symposium on Artificial Neural Networks, ESANN'04. D-Facto, 2004. PDF (preliminary version)


P. Geibel and F. Wysotzki: Perceptron Based Learning with Example Dependent and Noisy Costs. In: T. Fawcett, N. Mishra, editors, Proceedings of the International Conference on Machine Learning (ICML 03), pp. 218-225. Menlo Park, CA: AAAI Press, 2003. PDF