Ulf Brefeld
Prof. Dr.
- Informatics
- Business informatics
Research areas
- 2009
- Published
Feature selection for density level-sets
Kloft, M., Nakajima, S. & Brefeld, U., 2009, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Buntine, W., Grobelnik, M., Mladenic, D. & Shawe-Taylor, J. (eds.). Heidelberg: Springer, p. 692-704 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 5781 LNAI, no. PART 1).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- 2008
Automatic feature selection for anomaly detection
Kloft, M., Brefeld, U., Düssel, P., Gehl, C. & Laskov, P., 27.10.2008, Proceedings of the 1st ACM workshop on Workshop on AISec. Balfanz, D. & Staddon, J. (eds.). New York: Association for Computing Machinery, Inc, p. 71-76 6 p.Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
Exact and approximate inference for annotating graphs with structural SVMs
Klein, T., Brefeld, U. & Scheffer, T., 2008, Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008. Daelemans, W., Goethals, B. & Morik, K. (eds.). Berlin, Heidelberg: Springer, p. 611-623 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 5211 LNAI, no. PART 1).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- 2007
Supervised clustering of streaming data for email batch detection
Haider, P., Brefeld, U. & Scheffer, T., 2007, Proceedings of the 24th international conference on Machine learning. Ghahramani, Z. (ed.). New York: Association for Computing Machinery, Inc, p. 345-352 8 p.Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
Transductive support vector machines for structured variables
Zien, A., Brefeld, U. & Scheffer, T., 2007, Proceedings of the 24th international conference on Machine learning. New York: Association for Computing Machinery, Inc, p. 1183-1190 8 p.Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- 2006
Efficient co-regularised least squares regression
Brefeld, U., Gärtner, T., Scheffer, T. & Wrobel, S., 01.01.2006, Proceedings of the 23rd international conference on Machine learning. Cohen, W. (ed.). Association for Computing Machinery, Inc, p. 137-144 8 p. (ACM International Conference Proceeding Series; vol. 148).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
Semi-supervised learning for structured output variables
Brefeld, U. & Scheffer, T., 01.01.2006, Proceedings of the 23rd international conference on Machine learning. Cohen, W. & Moore, A. (eds.). Association for Computing Machinery, Inc, p. 145-152 8 p.Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- 2005
Systematic feature evaluation for gene name recognition
Hakenberg, J., Bickel, S., Plake, C., Brefeld, U., Zahn, H., Faulstich, L., Leser, U. & Scheffer, T., 24.05.2005, In: BMC Bioinformatics. 6, SUPPL.1, 11 p., S9.Research output: Journal contributions › Journal articles › Research › peer-review
Multi-view discriminative sequential learning
Brefeld, U., Büscher, C. & Scheffer, T., 01.01.2005, Machine Learning: ECML 2005: 16th European Conference on Machine Learning. Springer, p. 60-71 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 3720 LNAI).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
AUC Maximizing Support Vector Learning
Brefeld, U. & Scheffer, T., 2005, ROC Analysis in Machine Learning. 8 p.Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review