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Ulf Brefeld

Prof. Dr.

Ulf Brefeld

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Prof. Dr. Ulf Brefeld

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    1. 2005

    2. 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

    3. 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

    4. 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

    5. 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/works › Article in conference proceedings › Research › peer-review

    6. 2004
    7. 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/works › Article in conference proceedings › Research › peer-review

    8. 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 contributions › Journal articles › Research › peer-review

    9. 2003

    10. 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 contributions › Journal articles › Research › peer-review

    11. 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 contributions › Conference article in journal › Research › peer-review

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