| The spectacl of nonconvex clustering: A spectral approach to density-based clustering S Hess, W Duivesteijn, P Honysz, K Morik Proceedings of the AAAI conference on artificial intelligence 33 (01), 3788-3795, 2019 | 34 | 2019 |
| The PRIMPING routine—Tiling through proximal alternating linearized minimization S Hess, K Morik, N Piatkowski Data Mining and Knowledge Discovery 31 (4), 1090-1131, 2017 | 28 | 2017 |
| The relationship of DBSCAN to matrix factorization and spectral clustering E Schubert, S Hess, K Morik LWDA 2018-Lernen, Wissen, Daten, Analysen 2018, 330-334, 2018 | 24 | 2018 |
| Softmax-based classification is k-means clustering: Formal proof, consequences for adversarial attacks, and improvement through centroid based tailoring S Hess, W Duivesteijn, D Mocanu arXiv preprint arXiv:2001.01987, 2020 | 19 | 2020 |
| BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descent S Hess, G Pio, M Hochstenbach, M Ceci Data Mining and Knowledge Discovery 35 (6), 2542-2576, 2021 | 14 | 2021 |
| C-salt: Mining class-specific alterations in boolean matrix factorization S Hess, K Morik Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 11 | 2017 |
| k Is the Magic Number—Inferring the Number of Clusters Through Nonparametric Concentration Inequalities S Hess, W Duivesteijn Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020 | 10 | 2020 |
| The trustworthy pal: Controlling the false discovery rate in boolean matrix factorization S Hess, N Piatkowski, K Morik Proceedings of the 2018 SIAM International Conference on Data Mining, 405-413, 2018 | 10 | 2018 |
| Shrimp: descriptive patterns in a tree S Hess, N Piatkowski, K Morik 16th Workshops on Learning, Knowledge, Adaptation, LWA 2014: Knowledge …, 2014 | 6 | 2014 |
| A mathematical theory of making hard decisions: model selection and robustness of matrix factorization with binary constraints SC Heß | 4 | 2018 |
| Untersuchungen zur Analyse von deutschsprachigen Textdaten K Morik, A Jung, J Weckwerth, S Rötner, S Hess, S Buschjäger, L Pfahler Universitätsbibliothek Dortmund, 2015 | 3 | 2015 |
| Shrub ensembles for online classification S Buschjäger, S Hess, KJ Morik Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6123-6131, 2022 | 2 | 2022 |
| How to cheat the page limit W Duivesteijn, S Hess, X Du Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 10 (3 …, 2020 | 2 | 2020 |
| k is the magic number—supplementary material S Hess, W Duivesteijn arXiv, to appear, 2019 | 1 | 2019 |
| How to Cheat the Page Limit: the Version Adhering to the Guidelines W Duivesteijn, S Hess, X Du To appear, 0 | 1 | |
| How to Cheat the Page Limit: the Cheating Version W Duivesteijn, S Hess, X Du To appear, 0 | 1 | |
| Scoring Rule Nets: Beyond Mean Target Prediction in Multivariate Regression D Roordink, S Hess Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | | 2023 |
| Islands of Confidence: Robust Neural Network Classification with Uncertainty Quantification S Hess, T Huang, W Duivesteijn | | 2022 |
| Link Prediction for Free-Format Text D Majumdar, V Menkovski, S Hess, D Jarnikov, D Fahland | | 2020 |
| Punk Splits Tempers: On Characterizing Similarities and Differences of Labeled Data S Hess Technical report for Collaborative Research Center SFB 876 Providing …, 2016 | | 2016 |
Katharina MorikProfessor of Computer Science, TU Dortmund UniversityVerified email at tu-dortmund.de
