Holger Trittenbach
Holger Trittenbach
neurocat GmbH
Verified email at neurocat.ai - Homepage
Title
Cited by
Cited by
Year
HIPE: An energy-status-data set from industrial production
S Bischof, H Trittenbach, M Vollmer, D Werle, T Blank, K Böhm
Proceedings of the Ninth International Conference on Future Energy Systems …, 2018
142018
Dimension-based subspace search for outlier detection
H Trittenbach, K Böhm
International Journal of Data Science and Analytics 7 (2), 87-101, 2019
112019
An overview and a benchmark of active learning for outlier detection with One-Class classifiers
H Trittenbach, A Englhardt, K Böhm
Expert Systems with Applications, 114372, 2020
10*2020
Validating One-Class Active Learning with User Studies–a Prototype and Open Challenges
H Trittenbach, A Englhardt, K Böhm
ECML PKDD Workshop, 2019
72019
On the Tradeoff between Energy Data Aggregation and Clustering Quality
H Trittenbach, J Bach, K Böhm
Proceedings of the Ninth International Conference on Future Energy Systems …, 2018
52018
Towards Simulation-Data Science–A Case Study on Material Failures
H Trittenbach, M Gauch, K Böhm, K Schulz
2018 IEEE 5th International Conference on Data Science and Advanced …, 2018
42018
One-Class Active Learning for Outlier Detection with Multiple Subspaces
H Trittenbach, K Böhm
Proceedings of the 28th ACM International Conference on Information and …, 2019
32019
Active Learning of SVDD Hyperparameter Values
H Trittenbach, K Böhm, I Assent
2020 IEEE 7th International Conference on Data Science and Advanced …, 2020
22020
Energy Time-Series Features for Emerging Applications on the Basis of Human-Readable Machine Descriptions
M Vollmer, H Trittenbach, S Karrari, A Englhardt, P Bielski, K Böhm
Proceedings of the Tenth ACM International Conference on Future Energy …, 2019
22019
The Effect of Temporal Aggregation on Battery Sizing for Peak Shaving
D Werle, S Bischof, H Trittenbach, D Warzel, A Koziolek, K Böhm
Proceedings of the Tenth ACM International Conference on Future Energy …, 2019
22019
Finding the Sweet Spot: Batch Selection for One-Class Active Learning
A Englhardt, H Trittenbach, D Vetter, K Böhm
Proceedings of the 2020 SIAM International Conference on Data Mining, 118-126, 2020
12020
Data-driven crack assessment based on surface measurements
K Schulz, S Kreis, H Trittenbach, K Böhm
Engineering Fracture Mechanics 218, 106552, 2019
12019
Understanding the effects of temporal energy-data aggregation on clustering quality
H Trittenbach, J Bach, K Böhm
it-Information Technology 61 (2-3), 111-123, 2019
12019
Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary
A Englhardt, H Trittenbach, D Kottke, B Sick, K Böhm
arXiv preprint arXiv:2009.13853, 2020
2020
User-Centric Active Learning for Outlier Detection.
H Trittenbach
Karlsruhe Institute of Technology, Germany, 2020
2020
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Articles 1–15