Holger Trittenbach

According to our database, Holger Trittenbach authored at least 17 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Selecting Models based on the Risk of Damage Caused by Adversarial Attacks.

Jona Klemenc, Holger Trittenbach

CoRR, 2023

2022

An Empirical Evaluation of Constrained Feature Selection.

Jakob Bach, Kolja Zoller, Holger Trittenbach, Katrin Schulz, Klemens Böhm

SN Comput. Sci., 2022

Efficient SVDD sampling with approximation guarantees for the decision boundary.

Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm

Mach. Learn., 2022

Explaining Any ML Model? - On Goals and Capabilities of XAI.

Moritz Renftle, Holger Trittenbach, Michael Poznic, Reinhard Heil

CoRR, 2022

2021

An overview and a benchmark of active learning for outlier detection with one-class classifiers.

Holger Trittenbach, Adrian Englhardt, Klemens Böhm

Expert Syst. Appl., 2021

2020

User-Centric Active Learning for Outlier Detection.

Holger Trittenbach

PhD thesis, 2020

Finding the Sweet Spot: Batch Selection for One-Class Active Learning.

Adrian Englhardt, Holger Trittenbach, Dennis Vetter, Klemens Böhm

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Active Learning of SVDD Hyperparameter Values.

Holger Trittenbach, Klemens Böhm, Ira Assent

Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

2019

Understanding the effects of temporal energy-data aggregation on clustering quality.

Holger Trittenbach, Jakob Bach, Klemens Böhm

it Inf. Technol., 2019

Dimension-based subspace search for outlier detection.

Holger Trittenbach, Klemens Böhm

Int. J. Data Sci. Anal., 2019

The Effect of Temporal Aggregation on Battery Sizing for Peak Shaving.

Dominik Werle, Daniel Warzel, Simon Bischof, Anne Koziolek, Holger Trittenbach, Klemens Böhm

Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019

Energy Time-Series Features for Emerging Applications on the Basis of Human-Readable Machine Descriptions.

Michael Vollmer, Adrian Englhardt, Holger Trittenbach, Pawel Bielski, Shahab Karrari, Klemens Böhm

Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019

One-Class Active Learning for Outlier Detection with Multiple Subspaces.

Holger Trittenbach, Klemens Böhm

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018

An Overview and a Benchmark of Active Learning for One-Class Classification.

Holger Trittenbach, Adrian Englhardt, Klemens Böhm

CoRR, 2018

On the Tradeoff between Energy Data Aggregation and Clustering Quality.

Holger Trittenbach, Jakob Bach, Klemens Böhm

Proceedings of the Ninth International Conference on Future Energy Systems, 2018

HIPE: An Energy-Status-Data Set from Industrial Production.

Simon Bischof, Holger Trittenbach, Michael Vollmer, Dominik Werle, Thomas Blank, Klemens Böhm

Proceedings of the Ninth International Conference on Future Energy Systems, 2018

Towards Simulation-Data Science - A Case Study on Material Failures.

Holger Trittenbach, Martin Gauch, Klemens Böhm, Katrin Schulz

Proceedings of the 5th IEEE International Conference on Data Science and Advanced Analytics, 2018