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Ulf Brefeld

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Ulf Brefeld

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Prof. Dr. Ulf Brefeld

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    1. Published

      Action rate models for predicting actions in soccer

      Dick, U. & Brefeld, U., 02.03.2022, In: AStA Advances in Statistical Analysis. 107, 1-2, p. 29-49 21 p.

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

    2. Active and semi-supervised data domain description

      Görnitz, N., Kloft, M. & Brefeld, U., 01.07.2009, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, Proceedings, Part I. Buntine, W., Grobelnik, M., Mladenic, D. & Shawe-Taylor, J. (eds.). Berlin, Heidelberg: Springer, p. 407-422 16 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

    3. Published

      Active learning for network intrusion detection

      Görnitz, N., Kloft, M., Rieck, K. & Brefeld, U., 2009, AISec '09: Proceedings of the ACM Conference on Computer and Communications Security. Balfanz, D. & Staddon, J. (eds.). New York: Association for Computing Machinery, Inc, p. 47-54 8 p.

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

    4. Published

      Adaptive Item Selection Under Matroid Constraints

      Bengs, D., Brefeld, U. & Kröhne, U., 07.08.2018, In: Journal of Computerized Adaptive Testing. 6, 2, p. 15-36 22 p.

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

    5. Adaptive Speed Tests

      Bengs, D. & Brefeld, U., 2014, Proceedings of the German Workshop on Knowledge Discovery and Machine Learning. Henrich, A. & Sperker, H-C. (eds.). Bamberg: Lehrstuhl für Medieninformatik - Universität Bamberg, p. 86-90 4 p.

      Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research › peer-review

    6. Published

      Analysing Positional Data

      Brefeld, U., Mair, S. & Lasek, J., 01.10.2020, Science Meets Sports: When Statistics Are More Than Numbers. Ley, C. & Dominicy, Y. (eds.). Newcastle upon Tyne: Cambridge Scholars Publishing, p. 81-94 13 p. (Physical Sciences).

      Research output: Contributions to collected editions/works › Chapter › peer-review

    7. An Off-the-shelf Approach to Authorship Attribution

      Nasir, J. A., Görnitz, N. & Brefeld, U., 2014, COLING 2014 - 25th International Conference on Computational Linguistics, Proceedings of COLING 2014: Technical Papers. Dublin: Association for Computational Linguistics (ACL), p. 895-904 10 p. (COLING 2014 - 25th International Conference on Computational Linguistics, Proceedings of COLING 2014: Technical Papers).

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

    8. 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

    9. Published

      Assessing User Behavior by Mouse Movements

      Matthiesen, J. J. & Brefeld, U., 2020, HCI International 2020 - Posters - : 22nd International Conference, HCII 2020, Proceedings. Stephanidis, C. & Antona, M. (eds.). Cham: Springer, p. 68-75 8 p. (Communications in Computer and Information Science; vol. 1224 CCIS).

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

    10. 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

    11. 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

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

    13. 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

    14. Computer-based Adaptive Speed Tests

      Brefeld, U. & Bengs, D., 2014, The 7th International Conference on Educational Data Mining EDM 2014: Proceedings. Stamper, J., Pardos, Z., Mavrikis, M. & McLaren, B. M. (eds.). London, p. 221-224 4 p.

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

    15. Published

      Contextual movement models based on normalizing flows

      Fadel, S., Mair, S., da Silva Torres, R. & Brefeld, U., 03.2023, In: AStA Advances in Statistical Analysis. 107, 1-2, p. 51-72 22 p.

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

    16. Published

      Convolutional Neural Networks

      Rudolph, Y. & Brefeld, U., 01.01.2023, Sportinformatik: Modellbildung, Simulation, Datenanalyse und Visualisierung von sportbezogenen Daten. Memmert, D. (ed.). Berlin: Springer Spektrum, p. 207-215 9 p.

      Research output: Contributions to collected editions/works › Chapter

    17. Published

      Coresets for Archetypal Analysis

      Mair, S. & Brefeld, U., 2020, 32rd Conference on Neural Information Processing Systems (NeurIPS 2019): Vancouver, Canada, 8-14 December 2019. Wallach, H. & Larochelle, H. (eds.). Red Hook: Curran Associates, Vol. 10. p. 7215-7223 9 p. (Advances in neural information processing systems; vol. 32).

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

    18. 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

    19. Published

      Data practices in apps from Brazil: What do privacy policies inform us about?

      Quadros dos Reis, V., Rabello, M. E. R., Lima, A. C., Jardim, G. P. S., Fernandes, E. R. & Brefeld, U., 10.02.2023, In: Journal on Interactive Systems. 14, 1, p. 1-8 8 p.

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

    20. 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

    21. 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

    22. 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

    23. 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

    24. 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

    25. 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

    26. Eighth Workshop on Mining and Learning with Graphs

      Brefeld, U., Getoor, L. & Macskassy, S. A., 2010, In: ACM SIGKDD Explorations. 12, 2, p. 63-65 3 p.

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

    27. Published

      Evaluating one-shot tournament predictions

      Ekstrom, C. T., Van Eetvelde, H., Ley, C. & Brefeld, U., 05.04.2021, In: Journal of Sports Analytics. 7, 1, p. 37-46 10 p.

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

    28. 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

    29. 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

    30. 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

    31. 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

    32. 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

    33. 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

    34. Published

      Foreword to applied data science, demo, and nectar tracks

      Brefeld, U., Curry, E., Daly, E., Macnamee, B., Marascu, A. & Pinelli, F., 01.01.2019, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings. Brefeld, U., Curry, E., Daly, E., Macnamee, B., Marascu, A. & Pinelli, F. (eds.). Cham: Springer, Vol. 3. p. V-VI 2 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11053).

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

    35. 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

    36. Published

      Frame-based Optimal Design

      Mair, S., Rudolph, Y., Closius, V. & Brefeld, U., 23.01.2019, Machine learning and knowledge discovery in databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings. Berlingerio, M., Bonchi, F., Gärtner, T., Hurley, N. & Ifrim, G. (eds.). Cham: Springer Nature AG, Vol. 2. p. 447-463 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11052 LNAI).

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

    37. Generalising IRT to Discriminate Between Examinees

      Boubekki, A., Brefeld, U. & Delacroix, T., 2015, Proceedings of the International Conference on Educational Data Mining. Santos, O. C., Boticario, J. G., Romeo, C., Pechenizkiy, M., Merceron, A., Mitros, P., Luna, J. M., Mihaescu, C., Moreno, P., Hershkovitz, A., Ventura, S. & Desmarais, M. (eds.). Madrid: National University for Distance Education (UNED), p. 604-605 2 p.

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

    38. Graph-based Approaches for Analyzing Team Interaction on the Example of Soccer

      Brandt, M. & Brefeld, U., 2015, Proceedings of the 2th Workshop on Machine Learning and Data Mining for Sports Analytics - MLSA 2015. Davis, J. & Haaren, J. V. (eds.). Achen: Sun Site Central Europe (RWTH Aachen University), p. 10-17 8 p. (CEUR Workshop Proceedings; vol. 1970).

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

    39. Published

      Graph Conditional Variational Models: Too Complex for Multiagent Trajectories?

      Rudolph, Y., Brefeld, U. & Dick, U., 2020, In: Proceedings of Machine Learning Research. 137, p. 136-147 12 p.

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

    40. 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

    41. Published

      Hands in Focus: Sign Language Recognition Via Top-Down Attention

      Sarhan, N., Wilms, C., Closius, V., Brefeld, U. & Frintrop, S., 08.10.2023, 2023 IEEE International Conference on Image Processing, ICIP 2023 - Proceedings: Proceedings. Piscataway: IEEE Electromagnetic Compatibility Society, p. 2555-2559 5 p. (Proceedings - International Conference on Image Processing, ICIP).

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

    42. Hybrid models for future event prediction

      Amodeo, G., Blanco, R. & Brefeld, U., 2011, Proceedings of the 20th ACM international conference on Information and knowledge management. Berendt, B., de Vries, A., Fan, W., Macdonald, C., Ounis, I. & Ruthven, I. (eds.). New York: Association for Computing Machinery, Inc, p. 1981-1984 4 p.

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

    43. Published

      Infinite Mixtures of Markov Chains

      Reubold, J., Boubekki, A., Strufe, T. & Brefeld, U., 2018, New Frontiers in Mining Complex Patterns: 6th International Workshop, NFMCP 2017 : held in conjunction with ECML-PKDD 2017, Skopje, Macedonia, September 18-22, 2017 : revised selected papers. Appice, A., Loglisci, C., Manco, G. & Masciari, E. (eds.). Cham: Springer, p. 167-181 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10785 LNAI).

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

    44. Insights from classifying visual concepts with multiple kernel learning

      Binder, A., Nakajima, S., Kloft, M., Müller, C., Samek, W., Brefeld, U., Müller, K. R. & Kawanabe, M., 24.08.2012, In: PLoS ONE. 7, 8, e38897.

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

    45. Published

      Joint optimization of an autoencoder for clustering and embedding

      Boubekki, A., Kampffmeyer, M., Brefeld, U. & Jenssen, R., 01.07.2021, In: Machine Learning. 110, 7, p. 1901-1937 37 p.

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

    46. Learning from partially annotated sequences

      Fernandes, E. R. & Brefeld, U., 2011, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Proceedings. Gunopulos, D., Hofmann, T., Malerba, D. & Vazirgiannis, M. (eds.). PART 1 ed. Heidelberg, Berlin: Springer, p. 407-422 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 6911 LNAI, no. PART 1).

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

    47. 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

    48. Learning shortest paths in word graphs

      Tzouridis, E. & Brefeld, U., 2014, Knowledge Discovery, Data Mining and Machi- ne Learning (KDML-2013). Henrich, A. & Sperker, H-C. (eds.). Bamberg: Lehrstuhl für Medieninformatik - Universität Bamberg, p. 113-116 4 p.

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

    49. Learning to rank user intent

      Giannopoulos, G., Brefeld, U., Dalamagas, T. & Sellis, T., 2011, Proceedings of the 20th ACM international conference on Information and knowledge management . Association for Computing Machinery, Inc, p. 195-200 6 p.

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

    50. Published

      Learning to Rate Player Positioning in Soccer

      Dick, U. & Brefeld, U., 01.03.2019, In: Big Data. 7, 1, p. 71-82 12 p.

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

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