Ulf Brefeld

Prof. Dr.

  1. 2008
  2. 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/worksArticle in conference proceedingsResearchpeer-review

  3. 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/worksArticle in conference proceedingsResearchpeer-review

  4. 2007
  5. 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/worksArticle in conference proceedingsResearchpeer-review

  6. 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/worksArticle in conference proceedingsResearchpeer-review

  7. 2006
  8. 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/worksArticle in conference proceedingsResearchpeer-review

  9. 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/worksArticle in conference proceedingsResearchpeer-review

  10. 2005
  11. 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 contributionsJournal articlesResearchpeer-review

  12. 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/worksArticle in conference proceedingsResearchpeer-review

  13. AUC Maximizing Support Vector Learning

    Brefeld, U. & Scheffer, T., 2005, ROC Analysis in Machine Learning. 8 p.

    Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

  14. Multi-view hidden markov perceptrons

    Brefeld, U., Büscher, C. & Scheffer, T., 2005, Lernen, Wissensentdeckung und Adaptivitat, LWA 2005. Bauer, M., Brandherm, B., Fürnkranz, J., Grieser, G., Hotho, A., Jedlitschka, A. & Kröner, A. (eds.). Saarbrücken: Gesellschaft für Informatik e.V., p. 134-138 5 p.

    Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

  15. 2004
  16. Published

    Co-EM Support Vector learning

    Brefeld, U. & Scheffer, T., 2004, Proceeding ICML '04 Proceedings of the twenty-first international conference on Machine learning. New York: Association for Computing Machinery, Inc, p. 121-128 8 p. (Proceedings, Twenty-First International Conference on Machine Learning, ICML 2004).

    Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

  17. Perceptron and SVM learning with generalized cost models

    Geibel, P., Brefeld, U. & Wysotzki, F., 2004, In: Intelligent Data Analysis. 8, 5, p. 439-455 17 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  18. 2003
  19. Learning linear classifiers sensitive to example dependent and noisy costs

    Geibel, P., Brefeld, U. & Wysotzki, F., 01.01.2003, In: Lecture Notes in Computer Science. 2810, p. 167-178 12 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  20. Support vector machines with example dependent costs

    Brefeld, U., Geibel, P. & Wysotzki, F., 01.01.2003, In: Lecture Notes in Computer Science. 2837, p. 23-34 12 p.

    Research output: Journal contributionsConference article in journalResearchpeer-review

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