Sebastian Nusser

Publications

1. Nusser, S., Otte, C., Hauptmann, W., Kruse, R.: Learning verifiable ensembles for classification problems with high safety requirements. In Wang, L.S.L., Hong, T.P., eds.: Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technology. IGI Global (2010) 405-431
2. Nusser, S.: Robust Learning in Safety-Related Domains. PhD thesis, Otto-von-Guericke-Universität Magdeburg (July 2009)
3. Nusser, S., Otte, C., Hauptmann, W.: Multi-class extension of verifiable ensemble models for safety-related applications. In Fink, A., Lausen, B., Seidel, W., Ultsch, A., eds.: Advances in Data Analysis, Data Handling and Business Intelligence. Studies in Classification, Data Analysis, and Knowledge Organization, Springer (2009) 733–744
4. Nusser, S., Otte, C., Hauptmann, W.: Verifiable ensembles of low-dimensional submodels for multi-class problems with imbalanced misclassification costs. In Okun, O., Valentini, G., eds.: Applications of Supervised and Unsupervised Ensemble Methods. Volume 245 of Studies in Computational Intelligence. Springer (2009) 191–211
5. Nusser, S., Otte, C., Hauptmann, W., Leirich, O., Krätschmer, M., Kruse, R.: Maschinelles Lernen von validierbaren Klassifikatoren zur autonomen Steuerung sicherheitsrelevanter Systeme. at – Automatisierungstechnik 57(3) (2009) 138–145 (in German).
6. Nusser, S., Otte, C., Hauptmann, W.: An EM-based piecewise linear regression algorithm. In Corchado, E., Abraham, A., Pedrycz, W., eds.: Proceedings of 3rd International Workshop on Hybrid Artificial Intelligence Systems. Volume 5271 of Lecture Notes in Artificial Intelligence., Burgos, Spain, Springer (2008) 466–474
7. Nusser, S., Otte, C., Hauptmann, W.: Multi-class modeling with ensembles of local models for imbalanced misclassification costs. In Okun, O., Valentini, G., eds.: Proceedings of 2nd Workshop on Supervised and Unsupervised Ensemble Methods and Their Applications (at ECAI 2008), Patras, Greece (2008) 36–40
8. Nusser, S., Otte, C., Hauptmann, W.: Interpretable ensembles of local models for safety-related applications. In Verleysen, M., ed.: Proceedings of 16th European Symposium on Artificial Neural Networks, Brugge, Belgium, D-facto publications (2008) 301–306
9. Nusser, S., Otte, C., Hauptmann, W.: Learning binary classifiers for applications in safety-related domains. In Mikut, R., Reischl, M., eds.: Proceedings of 17th Workshop Computational Intelligence, Dortmund, Germany, Universitätsverlag Karlsruhe (2007) 139–151
10. Otte, C., Nusser, S., Hauptmann, W.: Machine learning methods for safety-related domains: Status and perspectives. In: Proceedings of Symposium on Fuzzy Systems in Computer Science, Magdeburg, Germany (2006) 139–148
11. Nusser, S.: Multiple testing error assessment for strongly dependent hypotheses using resampling. Master’s thesis, Otto-von-Guericke-Universität Magdeburg (September 2005)
12. Nusser, S.: Inductive causation based on binary data. Technical report, Otto-von-Guericke-Universität Magdeburg (October 2004)