Teaching

• Stochastics 0 (Universität Marburg, Winter 05/06)


• Mathematics III (Universität Marburg, Winter 04/05)


• Mathematics II (Universität Marburg, Summer 04)


• Mathematics III (Universität Marburg, Winter 03/04)


• Mathematics II (Universität Marburg, Summer 03)

Publications

• M. Kloft, U. Brefeld, S. Sonnenburg, P. Laskov, K.-R. Müller, and A. Zien. Efficient and Accurate Lp-norm Multiple Kernel Learning. Advances in Neural Information Processing Systems, (to appear) 2010.

• S. Nakajima, A. Binder, C. Müller, W. Wojcikiewicz, M. Kloft, U. Brefeld, K.-R. Müller, and M. Kawanabe. Multiple Kernel Learning for Object Classification. Proceedings of the 12th Workshop on Information-based Induction Sciences, 2009.

• N. Görnitz, M. Kloft, K. Rieck, and U. Brefeld. Active Learning for Network Intrusion Detection*. Proceedings of the 2nd ACM Workshop on Security and Artificial Intelligence (AISEC), (to appear) 2009.

• P. Laskov, M. Kloft. A Framework for Quantitative Security Analysis of Machine Learning*. Proceedings of the 2nd ACM Workshop on Security and Artificial Intelligence (AISEC), (to appear) 2009.

• R. Jenssen, M. Kloft, A. Zien, S. Sonnenburg, and K.-R. Müller. A Multi-Class Support Vector Machine based on Scatter Criteria. Technical Report 14/2009, Technische Universität Berlin, 2009.

• N. Görnitz and M. Kloft, and U. Brefeld. Active and Semi-supervised Data Domain Description**. Proceedings of the European Conference on Machine Learning (ECML), 2009.

• M. Kloft, S. Nakajima, and U. Brefeld. Feature Selection for Density Level-Sets**. Proceedings of the European Conference on Machine Learning (ECML), 2009.

• M. Kloft, U. Brefeld, S. Sonnenburg, A. Zien, P. Laskov, and K.-R. Müller. Learning Non-sparse Kernel Mixtures. Proceedings of the PASCAL2 Workshop on Sparsity in Machine Learning and Statistics, 2009.

• M. Kloft, U. Brefeld, P. Laskov, and S. Sonnenburg. Non-sparse Multiple Kernel Learning. Proceedings of the NIPS Workshop on Kernel Learning: Automatic Selection of Optimal Kernels, 2008.

• M. Kloft, U. Brefeld, P. Düssel, C. Gehl, and P. Laskov. Automatic Feature Selection for Anomaly Detection*. Proceedings of the 1st ACM Workshop on Security and Artificial Intelligence (AISEC), 2008.

• M. Kloft and P. Laskov. A “Poisoning ” Attack Against Online Anomaly Detection. Proceedings of the NIPS Workshop on Machine Learning in Adversarial Environments, 2007.

• M. Kloft. Stabile Basisorte und der Satz von Zariski-Fujita. Diplomarbeit. Universität Marburg, 2006.