Rückert, U and Kramer, S (2006).
Margin-Based First-Order Rule Learning
In: Proceedings of the 16th International Conference on Inductive Logic Programming (ILP 2006), ed. by S. Muggleton, R. Otero, and A. Tamaddoni-Nezhad, pp. 46-48, Berlin, Springer. Lecture Notes in Computer Science Vol. 4455.

Georgii, E, Richter, L, Rückert, U, and Kramer, S (2005).
Analyzing Microarray Data Using Quantitative Association Rules
Bioinformatics, 21(2):ii1-ii8.

Brinkmann, A, Heidebuer, M, Heide, FMad, Rückert, U, Salzwedel, K, and Vodisek, M (2004).
V:Drive - Costs and Benefits of an Out-of-Band Storage Virtualization System
In: Proceedings of the 12th NASA Goddard, 21st IEEE Conference on Mass Storage Systems and Technologies (MSST), pp. 153 - 157, College Park, Maryland, USA.

Löser, C, Brinkmann, A, and Rückert, U (2004).
Distributed Path Selection (DPS): A Traffic Engineering Protocol for IP-Networks
In: Proceedings of the Thirty-Seventh Hawaii International Conference on System Sciences (HICSS-37), Big Island, Hawaii, USA.

Rückert, U and Kramer, S (2004).
Frequent Free Tree Discovery in Graph Data
In: Proceedings of the ACM Symposium on Applied Computing (SAC-2004), pp. 564-570.

Rückert, U and Kramer, S (2004).
Towards Tight Bounds for Rule Learning
In: Proceedings of the 21st International Conference on Machine Learning (ICML-2004), pp. 711-718, ACM Press.

Rückert, U, Richter, L, and Kramer, S (2004).
Quantitative Association Rules Based on Half-Spaces: An Optimization Approach
In: Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM-2004), vol. 00, pp. 507-510, Los Alamitos, CA, USA, IEEE Computer Society Press.

Rückert, U, Richter, L, and Kramer, S (2004).
Quantitative Association Rules Based on Half-Spaces
Technische Universität München, München.

Brinkmann, A, Meyer auf der Heide, F, Salzwedel, K, Scheideler, C, Vodisek, M, and Rückert, U (2003).
Storage Management as Means to cope with Exponential Information Growth
In: Proceedings of International Conferences on Advances in Infrastructure for Electronic Business, Education, Science, Medicine, and Mobile Technologies on the Internet (SSGRR), L'Aquila, Italy.

Rückert, U and Kramer, S (2003).
Stochastic Local Search in k-Term DNF Learning
In: Proceedings of the Twentieth International Conference on Machine Learning (ICML 2003), ed. by T. Fawcett and N. Mishra, pp. 648-655, AAAI Press.