Principled Interpolation in Normalizing Flows

Fadel, S., Mair, S., da Silva Torres, R. & Brefeld, U., 09.2021, Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part II. Oliver, N., Pérez-Cruz, F., Kramer, S., Read, J. & Lozano, J. A. (eds.). Cham: Springer Nature AG, p. 116-131 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12976 LNAI).

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

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

HyperUCB: Hyperparameter optimization using contextual bandits

Tavakol, M., Mair, S. & Morik, K., 28.03.2020, Machine Learning and Knowledge Discovery in Databases: International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part I. Cellier, P. & Driessens, K. (eds.). Cham: Springer Nature AG, Vol. 1. p. 44-50 7 p. ( Communications in Computer and Information Science; vol. 1167).

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

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

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

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

Universal Threshold Calculation for Fingerprinting Decoders using Mixture Models

Schäfer, M., Mair, S., Berchtold, W. & Steinebach, M., 17.06.2015, Proceedings of the 3rd ACM Workshop on Information Hiding and Multimedia Security. Association for Computing Machinery, Inc, p. 109-114 6 p. (IH and MMSec 2015 - Proceedings of the 2015 ACM Workshop on Information Hiding and Multimedia Security).

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