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Holger Trittenbach
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2020 – today
- 2024
- [i6]Felix Assion, Florens Greßner, Nitin Augustine, Jona Klemenc, Ahmed Hammam, Alexandre Krattinger, Holger Trittenbach, Sascha Riemer:
A-BDD: Leveraging Data Augmentations for Safe Autonomous Driving in Adverse Weather and Lighting. CoRR abs/2408.06071 (2024) - 2023
- [i5]Jona Klemenc
, Holger Trittenbach:
Selecting Models based on the Risk of Damage Caused by Adversarial Attacks. CoRR abs/2301.12151 (2023) - 2022
- [j5]Adrian Englhardt
Efficient SVDD sampling with approximation guarantees for the decision boundary. Mach. Learn. 111(4): 1349-1375 (2022) - [j4]Jakob Bach
An Empirical Evaluation of Constrained Feature Selection. SN Comput. Sci. 3(6): 445 (2022) - [i4]Moritz Renftle, Holger Trittenbach, Michael Poznic, Reinhard Heil:
Explaining Any ML Model? - On Goals and Capabilities of XAI. CoRR abs/2206.13888 (2022) - 2021
- [j3]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: 114372 (2021) - 2020
- [b1]Holger Trittenbach:
User-Centric Active Learning for Outlier Detection. Karlsruhe Institute of Technology, Germany, 2020 - [c8]Holger Trittenbach, Klemens Böhm, Ira Assent
Active Learning of SVDD Hyperparameter Values. DSAA 2020: 109-117 - [c7]Adrian Englhardt, Holger Trittenbach, Dennis Vetter
Finding the Sweet Spot: Batch Selection for One-Class Active Learning. SDM 2020: 118-126 - [i3]Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm:
Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary. CoRR abs/2009.13853 (2020)
2010 – 2019
- 2019
- [j2]Holger Trittenbach
Dimension-based subspace search for outlier detection. Int. J. Data Sci. Anal. 7(2): 87-101 (2019) - [j1]Holger Trittenbach
Understanding the effects of temporal energy-data aggregation on clustering quality. it Inf. Technol. 61(2-3): 111-123 (2019) - [c6]Holger Trittenbach, Klemens Böhm:
One-Class Active Learning for Outlier Detection with Multiple Subspaces. CIKM 2019: 811-820 - [c5]Michael Vollmer, Adrian Englhardt, Holger Trittenbach, Pawel Bielski
Energy Time-Series Features for Emerging Applications on the Basis of Human-Readable Machine Descriptions. e-Energy 2019: 474-481 - [c4]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: 482-485 - [i2]Holger Trittenbach, Klemens Böhm, Ira Assent:
Active Learning of SVDD Hyperparameter Values. CoRR abs/1912.01927 (2019) - 2018
- [c3]Holger Trittenbach, Martin Gauch, Klemens Böhm, Katrin Schulz:
Towards Simulation-Data Science - A Case Study on Material Failures. DSAA 2018: 450-459 - [c2]Holger Trittenbach, Jakob Bach
On the Tradeoff between Energy Data Aggregation and Clustering Quality. e-Energy 2018: 399-401 - [c1]Simon Bischof, Holger Trittenbach, Michael Vollmer, Dominik Werle, Thomas Blank, Klemens Böhm:
HIPE: An Energy-Status-Data Set from Industrial Production. e-Energy 2018: 599-603 - [i1]Holger Trittenbach, Adrian Englhardt, Klemens Böhm:
An Overview and a Benchmark of Active Learning for One-Class Classification. CoRR abs/1808.04759 (2018)
Coauthor Index
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last updated on 2024-10-07 21:22 CEST by the dblp team
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