Holger Trittenbach

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 18

Top Topics

Temporal Aggregation

Feature Selection

Outlier Detection

Active Learning

Top Venues

Publications

Jona Klemenc, Holger Trittenbach
Selecting Models based on the Risk of Damage Caused by Adversarial Attacks. CoRR (2023)
Jakob Bach, Kolja Zoller, Holger Trittenbach, Katrin Schulz, Klemens Böhm
An Empirical Evaluation of Constrained Feature Selection. SN Comput. Sci. 3 (6) (2022)
Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm
Efficient SVDD sampling with approximation guarantees for the decision boundary. Mach. Learn. 111 (4) (2022)
Moritz Renftle, Holger Trittenbach, Michael Poznic, Reinhard Heil
Explaining Any ML Model? - On Goals and Capabilities of XAI. CoRR (2022)
Holger Trittenbach, Adrian Englhardt, Klemens Böhm
An overview and a benchmark of active learning for outlier detection with one-class classifiers. Expert Syst. Appl. 168 (2021)
Adrian Englhardt, Holger Trittenbach, Dennis Vetter, Klemens Böhm
Finding the Sweet Spot: Batch Selection for One-Class Active Learning. SDM (2020)
Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm
Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary. CoRR (2020)
Holger Trittenbach, Klemens Böhm, Ira Assent
Active Learning of SVDD Hyperparameter Values. DSAA (2020)
Holger Trittenbach, Klemens Böhm
Dimension-based subspace search for outlier detection. Int. J. Data Sci. Anal. 7 (2) (2019)
Holger Trittenbach, Jakob Bach, Klemens Böhm
Understanding the effects of temporal energy-data aggregation on clustering quality. it Inf. Technol. 61 (2-3) (2019)
Michael Vollmer, Adrian Englhardt, Holger Trittenbach, Pawel Bielski, Shahab Karrari, Klemens Böhm
Energy Time-Series Features for Emerging Applications on the Basis of Human-Readable Machine Descriptions. e-Energy (2019)
Dominik Werle, Daniel Warzel, Simon Bischof, Anne Koziolek, Holger Trittenbach, Klemens Böhm
The Effect of Temporal Aggregation on Battery Sizing for Peak Shaving. e-Energy (2019)
Holger Trittenbach, Klemens Böhm, Ira Assent
Active Learning of SVDD Hyperparameter Values. CoRR (2019)
Holger Trittenbach, Klemens Böhm
One-Class Active Learning for Outlier Detection with Multiple Subspaces. CIKM (2019)
Holger Trittenbach, Jakob Bach, Klemens Böhm
On the Tradeoff between Energy Data Aggregation and Clustering Quality. e-Energy (2018)
Holger Trittenbach, Adrian Englhardt, Klemens Böhm
An Overview and a Benchmark of Active Learning for One-Class Classification. CoRR (2018)
Holger Trittenbach, Martin Gauch, Klemens Böhm, Katrin Schulz
Towards Simulation-Data Science - A Case Study on Material Failures. DSAA (2018)
Simon Bischof, Holger Trittenbach, Michael Vollmer, Dominik Werle, Thomas Blank, Klemens Böhm
HIPE: An Energy-Status-Data Set from Industrial Production. e-Energy (2018)