Professorship for Information Systems, in particular Machine Learning
Organisational unit: Professoship
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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Semi-Supervised Generative Models for Multi-Agent Trajectories
Brefeld, U., Fassmeyer, D. & Fassmeyer, P., 2022, Advances in Neural Information Processing Systems 35: 36th Conference on Neural Information Processing Systems (NeurIPS 2022). Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). Red Hook: Curran Associates, Vol. 48. p. 37267-37281 15 p. (Advances in Neural Information Processing Systems; vol. 35).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Modeling Conditional Dependencies in Multiagent Trajectories
Rudolph, Y. & Brefeld, U., 2022, In: Proceedings of Machine Learning Research. 151, p. 10518-10533 16 p.Research output: Journal contributions › Conference article in journal › Research › peer-review
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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
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FaST: A linear time stack trace alignment heuristic for crash report deduplication
Rodrigues, I. M., Aloise, D. & Fernandes, E. R., 17.10.2022, The 2022 Mining Software Repositories Conference: MSR 2022, Proceedings; 18-20 May 2022, Virtual; 23-24 May 2022, Pittsburgh, Pennsylvania. New York: Institute of Electrical and Electronics Engineers Inc., p. 549-560 12 p. (Proceedings - IEEE/ACM International Conference on Mining Software Repositories ).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Who can receive the pass? A computational model for quantifying availability in soccer
Dick, U., Link, D. & Brefeld, U., 01.05.2022, In: Data Mining and Knowledge Discovery. 36, 3, p. 987-1014 28 p.Research output: Journal contributions › Journal articles › Research › peer-review
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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
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Rating Player Actions in Soccer
Dick, U., Tavakol, M. & Brefeld, U., 15.07.2021, In: Frontiers in Sports and Active Living. 3, 14 p., 682986.Research output: Journal contributions › Journal articles › Research › peer-review
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Toward Automatically Labeling Situations in Soccer
Fassmeyer, D., Anzer, G., Bauer, P. & Brefeld, U., 03.11.2021, In: Frontiers in Sports and Active Living. 3, 15 p., 725431.Research output: Journal contributions › Journal articles › Research › peer-review
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Machine Learning and Data Mining for Sports Analytics: 7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings
Brefeld, U. (Editor), Davis, J. (Editor), van Haaren, J. (Editor) & Zimmermann, A. (Editor), 2020, Cham: Springer International Publishing. 146 p. (Communications in Computer and Information Science; vol. 1324)Research output: Books and anthologies › Conference proceedings › Research
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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part III
Brefeld, U. (Editor), Fromont, E. (Editor), Hotho, A. (Editor), Knobbe, A. (Editor), Maathuis, M. (Editor) & Robardet, C. (Editor), 2020, Cham: Springer Nature Switzerland AG. 804 p. (Lecture notes in computer science; vol. 11906)(Lecture Notes in Artificial Intelligence; vol. 11906)Research output: Books and anthologies › Conference proceedings › Research