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Professorship for Information Systems, in particular Machine Learning

Organisational unit: Professoship

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Main research areas

Research

We are interested in statistical machine learning with a focus on spatiotemporal problems, such as user navigation on the web, adaptive testing and adaptive learning environments, and the coordination of football players on the pitch. While we mainly focus on basic research, we also collaborate with selected partners in academia, sports and industry in different projects.

Teaching

Our teaching focuses on introductory/advanced machine learning and data mining as well as basic statistics. We regularly offer courses in the Management & Data Science Master and the Information Systems Bachelor programs. Exemplary courses comprise Deep Learning (Data Science), Statistics (Information Systems), and Machine Learning & Data Mining (Engineering).

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  1. 2018
  2. Published

    MDP-based itinerary recommendation using geo-tagged social media

    Gaonkar, R., Tavakol, M. & Brefeld, U., 25.10.2018, Advances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, Proceedings. Duivesteijn, W., Siebes, A. & Ukkonen, A. (eds.). Basel: Springer Nature AG, p. 111-123 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); no. 11191).

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

  3. Published

    Exploiting ConvNet diversity for flooding identification

    Nogueira, K., Fadel, S. G., Dourado, I. C., De Werneck, R. O., Munoz, J. A. V., Penatti, O. A. B., Calumby, R. T., Li, L. T., Dos Santos, J. A. & Torres, R. D. S., 09.2018, In: IEEE Geoscience and Remote Sensing Letters. 15, 9, p. 1446-1450 5 p., 8398414.

    Research output: Journal contributions › Journal articles › 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. 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

    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

  7. 2017
  8. 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

  9. 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

  10. 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

  11. 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

  12. 2016
  13. Published

    Predicting the future performance of soccer players

    Arndt, C. & Brefeld, U., 01.10.2016, In: Statistical Analysis and Data Mining. 9, 5, p. 373-382 10 p.

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

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