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Stefan Kramer, Prof. Dr.

Stefan Kramer, Prof. Dr.

Head of Information Systems

Room: 03-617
Johannes Gutenberg - Universität Mainz
Institut für Informatik
Staudingerweg 9

55128 Mainz, Germany

Office Phone: +49-6131-39-21057
Fax number: +49-6131-39-23534



Awards:

  • Best Application Paper Runner-Up, Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2001) (for: Kramer S., De Raedt L., Helma C.: Molecular Feature Mining in HIV Data)
  • Best Theory Paper, 16th International Conference on Inductive Logic Programming (ILP-2006) (for: Rückert U., Kramer S.: Margin-Based First-Order Rule Learning)
  • Best Application Paper, 8th IEEE International Conference on Data Mining (ICDM-2008) (for: Hapfelmeier A., Schmidt J., Mueller M., Drzezga A., Perneczky R., Kurz A., Kramer S.: Interpreting PET Scans by Structured
    Patient Data: A Data Mining Case Study in Dementia Research)

Activities:


Publications:

Girschick, T, Rückert, U, and Kramer, S (accepted).
Adapted Transfer of Distance Measures for Quantitative Structure-Activity Relationships and Data-Driven Selection of Source Datasets
The Computer Journal.

Schmidt, J, Hapfelmeier, A, Ghorbani, A, and Kramer, S (2013).
Learning Probabilistic Real-Time Automata from Multi-Attribute Event Logs
Intelligent Data Analysis Special Issue on Dynak Topics, 7(1):to appear.

Böck, M, Ogishima, S, Tanaka, H, Kramer, S, and Kaderali, L (2012).
Hub-Centered Gene Network Reconstruction using Automatic Relevance Determination
PLoS ONE, 7(5):e35077.

Duchrow, T, Schröer, M, Griesbach, B, Kasperski, S, Maas genannt Bermpohl, G, Kramer, S, and Kirchner, F (2012).
Towards Electric Mobility Data Mining
In: IEEE International Electric Vehicle Conference, IEVC 2012, pp. in press, IEEE.

Ganzert, S, Kramer, S, and Guttmann, J (2012).
Predicting the lung compliance of mechanically ventilated patients via statistical modeling
Physiological Measurement, 33:345-359.

Gütlein, M, Karwath, A, and Kramer, S (2012).
CheS-Mapper – Chemical Space Mapping and Visualization in 3D
Journal of Cheminformatics, 4(7).

Schmidt, J, Ansorge, S, and Kramer, S (2012).
Scalable Induction of Probabilistic Real-Time Automata Using Maximum Frequent Pattern Based Clustering
In: Proceedings of the twelfth SIAM International Conference on Data Mining, pp. to appear, SIAM / Omnipress.

Seeland, M, Pfahringer, B, and Kramer, S (2012).
Maximum Common Subgraph Based Locally Weighted Regression
In: Proceedings of the 27th Symposium On Applied Computing, pp. 484-491.

Wicker, J, Pfahringer, B, and Kramer, S (2012).
Multi-Label Classification using Boolean Matrix Decomposition
In: Proceedings of the 27th Symposium On Applied Computing, pp. 498-505, ACM.

Alphonse, E, Girschick, T, Buchwald, F, and Kramer, S (2011).
A Numerical Refinement Operator based on Multi-Instance Learning
In: Inductive Logic Programming - 20th International Conference, ILP 2010, ed. by Paolo Frasconi and Francesca A. Lisi, vol. 6489, pp. 14-21, Springer. LNCS/LNAI.


Selected Talks and Tutorials: