• 16 Citations
20142019

Research output per year

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Research Output

  • 16 Citations
  • 3 Chapter
  • 3 Conference contribution
  • 1 Article

k is the magic number: inferring the number of clusters through nonparametric concentration inequalities

Hess, S. & Duivesteijn, W., 2019, (Accepted/In press) Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) 2019.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

  • The SpectACl of nonconvex clustering: a spectral approach to density-based clustering.

    Hess, S., Duivesteijn, W., Honysz, P. & Morik, K., 2019, Proceedings of 33rd AAAI Conference on Artificial IntelligenceAAAI. Association for the Advancement of Artificial Intelligence, 27 p.

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

    Open Access
    File
  • The relationship of DBSCAN to matrix factorization and spectral clustering

    Schubert, E., Hess, S. & Morik, K., 2018, LWDA 2018 - Lernen, Wissen, Daten, Analysen 2018: Proceedings of the conference "Lernen, Wissen, Daten Analysen. Aachen: RWTH Aachen, p. 330-334 5 p. (CEUR workshop proceedings; vol. 2191).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Open Access
    File
  • The trustworthy pal: controlling the false discovery rate in boolean matrix factorization

    Hess, S., Piatkowski, N. & Morik, K., 2018, Proceedings of the 2018 SIAM International Conference on Data Mining. Philadelphia : Society for Industrial and Applied Mathematics (SIAM), p. 405-413 9 p.

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

    Open Access
    File
  • 1 Citation (Scopus)
    5 Downloads (Pure)

    C-salt: mining class-specific alterations in boolean matrix factorization

    Hess, S. & Morik, K., 2017, Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Ceci, M., Dzeroski, S., Vens, C., Todorovski, L. & Hollmen, J. (eds.). Cham: Springer, p. 547-563 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10534 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

    Open Access
    File
  • 3 Citations (Scopus)
    6 Downloads (Pure)

    Courses

    Student theses

    Anomaly detection on vibration data

    Author: Siganos, A., 28 Oct 2019

    Supervisor: Hess, S. (Supervisor 1), Pechenizkiy, M. (Supervisor 2), Yakovets, N. (Supervisor 2) & Uusitalo, J. (External person) (External coach)

    Student thesis: Master

    File