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  1. 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

  2. Published

    Stoffstrommanagement

    Möller, A., 2004, In: VDI Berichte. 1822, p. 51-59+97

    Research output: Journal contributions › Journal articles › Research › peer-review

  3. 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

  4. 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

  5. Using an adaptive memory strategy to improve a multistart heuristic for sequencing by hybridization

    Fernandes, E. R. & Ribeiro, C. C., 01.01.2005, Experimental and Efficient Algorithms: 4th International Workshop, WEA 2005, Santorini Island, Greece, May 10-13, 2005; Proceedings. Nikoletseas, S. E. (ed.). Berlin: Springer, p. 4-15 12 p. (Lecture Notes in Computer Science; vol. 3503).

    Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

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