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Ulf Brefeld

Prof. Dr.

Ulf Brefeld

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Prof. Dr. Ulf Brefeld

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    41 - 50 out of 94Page size: 10
    1. Published

      Probabilistic movement models and zones of control

      Brefeld, U., Lasek, J. & Mair, S., 15.01.2019, In: Machine Learning. 108, 1, p. 127-147 21 p.

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

    2. Published

      Propagating Maximum Capacities for Recommendation

      Boubekki, A., Brefeld, U., Lucchesi, C. L. & Stille, W., 2017, KI 2017: Advances in Artificial Intelligence: 40th Annual German Conference on AI, Dortmund, Germany, September 25-29, 2017 : proceedings. Cham, Schweiz: Springer, p. 72-84 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10505 LNAI).

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

    3. Published

      Guest editorial: Special issue on sports analytics

      Brefeld, U. & Zimmermann, A., 01.11.2017, In: Data Mining and Knowledge Discovery. 31, 6, p. 1577-1579 3 p.

      Research output: Journal contributions › Other (editorial matter etc.) › Research

    4. Published

      Frame-based Data Factorizations

      Mair, S., Boubekki, A. & Brefeld, U., 25.07.2017, 34th International Conference on Machine Learning, ICML 2017. Precup, D. & Teh, Y. W. (eds.). Red Hook: Curran Associates, p. 2305-2313 9 p. (Proceedings of Machine Learning Research; vol. 70).

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

    5. Published

      Distributed robust Gaussian Process regression

      Mair, S. & Brefeld, U., 01.05.2018, In: Knowledge and Information Systems. 55, 2, p. 415-435 21 p.

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

    6. Published

      A Unified Contextual Bandit Framework for Long- and Short-Term Recommendations

      Tavakol, M. & Brefeld, U., 30.12.2017, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2017 Skopje, Macedonia, September 18 – 22, 2017; Proceedings, Part II. Ceci, M., Hollmen, J., Todorovski, L., Vens, C. & Dzeroski, S. (eds.). Springer, Vol. 2. p. 269-284 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10535 LNAI).

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

    7. Published

      Data-driven analyses of electronic text books

      Boubekki, A., Kröhne, U., Goldhammer, F., Schreiber, W. & Brefeld, U., 2016, Solving large scale learning tasks: Challenges and algorithms : essays dedicated to Katharina Morik on the occasion of her 60th birthday. Michaelis, S., Piatkowski, N. & Stolpe, M. (eds.). Cham: Springer International Publishing AG, p. 362-376 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9580).

      Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research

    8. Published

      Feature Extraction and Aggregation for Predicting the Euro 2016

      Tavakol, M., Zafartavanaelmi, H. & Brefeld, U., 09.2016, In: CEUR Workshop Proceedings. 1842, 1842, 7 p.

      Research output: Journal contributions › Conference article in journal › Research › peer-review

    9. Efficient and accurate ℓ p-norm multiple kernel learning

      Kloft, M., Brefeld, U., Sonnenburg, S., Laskov, P., Müller, K. R. & Zien, A., 2009, Advances in Neural Information Processing Systems 22 : Proceedings of the 23rd Annual Conference on Neural Information Processing Systems 2009. Bengio, Y., Schuurmans, D., Lafferty, J., Williams, C. & Culotta, A. (eds.). Neural Information Processing Systems, p. 997-1005 9 p. (Advances in Neural Information Processing Systems; vol. 22).

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

    10. Approximate tree kernels

      Rieck, K., Krueger, T., Brefeld, U. & Müller, K. R., 02.2010, In: Journal of Machine Learning Research. 11, p. 555-580 26 p.

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

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