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Ulf Brefeld

Prof. Dr.

Ulf Brefeld

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Prof. Dr. Ulf Brefeld

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    1. Article in conference proceedings › Research › Peer-reviewed

    2. Discriminative clustering for market segmentation

      Haider, P., Chiarandini, L. & Brefeld, U., 2012, Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining. New York: Association for Computing Machinery, Inc, p. 417-425 9 p.

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

    3. Document assignment in multi-site search engines

      Brefeld, U., Barla Cambazoglu, B. & Junqueira, F. R., 2011, Proceedings of the fourth ACM international conference on Web search and data mining . New York: Association for Computing Machinery, Inc, p. 575-584 10 p.

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

    4. 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

    5. Efficient Classification of Images with Taxonomies

      Binder, A., Kawanabe, M. & Brefeld, U., 2010, Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Berlin, Heidelberg: Springer, p. 351-362 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 5996 LNCS, no. PART 3).

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

    6. 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

    7. 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

    8. Published

      Exploring the Poincaré Ellipsis

      Fadel, S., Paulsen, T. & Brefeld, U., 09.2023, 20th Machine Learning on Graphs workshop.

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

    9. Factored MDPs for detecting topics of user sessions

      Tavakol, M. & Brefeld, U., 06.10.2014, RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems. Association for Computing Machinery, Inc, p. 33-40 8 p.

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

    10. 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

    11. Finding Similar Movements in Positional Data Streams

      Haase, J. & Brefeld, U., 2013, Machine Learning and Data Mining for Sports Analytics - MLSA 2013: Proceedings. Jesse, D., Van Haaren, J. & Zimmermann, A. (eds.). Prag: Sun Site Central Europe (RWTH Aachen University), p. 49-57 9 p. (CEUR Workshop Proceedings; no. 1969).

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

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