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ORCIDHelena Kotthaus
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- affiliation: TU Dortmund University, Department of Computer Science, Germany
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2020 – today
- 2023
[c10]Hanxiao Tan, Helena Kotthaus:
Explainability-Aware One Point Attack for Point Cloud Neural Networks. WACV 2023: 4570-4579- 2022
- [j2]Katharina Morik, Helena Kotthaus, Raphael Fischer, Sascha Mücke, Matthias Jakobs, Nico Piatkowski, Andreas Pauly, Lukas Heppe, Danny Heinrich:
Yes we care!-Certification for machine learning methods through the care label framework. Frontiers Artif. Intell. 5 (2022) - [c9]Matthias Jakobs, Helena Kotthaus, Ines Röder, Maximilian Baritz:
SancScreen: Towards a Real-world Dataset for Evaluating Explainability Methods. LWDA 2022: 33-44 - [c8]Hanxiao Tan, Helena Kotthaus:
Surrogate Model-Based Explainability Methods for Point Cloud NNs. WACV 2022: 2927-2936 - [p2]Helena Kotthaus, Peter Marwedel:
Optimization of ML on Modern Multicore Systems. Mach. Learn. under Resour. Constraints Vol. 1 (1) 2022: 285-304 - [p1]Helena Kotthaus, Peter Marwedel:
Efficient Memory Footprint Reduction. Mach. Learn. under Resour. Constraints Vol. 1 (1) 2022: 306-324 - 2021
- [c7]Pierre Haritz, Lukas Pfahler, Thomas Liebig
, Helena Kotthaus:
Self-Supervised Source Code Annotation from Related Research Papers. ICDM (Workshops) 2021: 1083-1084 - [i4]Katharina Morik, Helena Kotthaus, Lukas Heppe, Danny Heinrich, Raphael Fischer, Sascha Mücke, Andreas Pauly, Matthias Jakobs, Nico Piatkowski:
Yes We Care! - Certification for Machine Learning Methods through the Care Label Framework. CoRR abs/2105.10197 (2021) - [i3]Katharina Morik, Helena Kotthaus, Lukas Heppe, Danny Heinrich, Raphael Fischer, Andreas Pauly, Nico Piatkowski:
The Care Label Concept: A Certification Suite for Trustworthy and Resource-Aware Machine Learning. CoRR abs/2106.00512 (2021) - [i2]Hanxiao Tan, Helena Kotthaus:
Surrogate Model-Based Explainability Methods for Point Cloud NNs. CoRR abs/2107.13459 (2021) - [i1]Hanxiao Tan, Helena Kotthaus:
Explainability-Aware One Point Attack for Point Cloud Neural Networks. CoRR abs/2110.04158 (2021)
2010 – 2019
- 2019
- [j1]Pinar Tözün, Helena Kotthaus:
Scheduling Data-Intensive Tasks on Heterogeneous Many Cores. IEEE Data Eng. Bull. 42(1): 61-72 (2019) - [c6]Helena Kotthaus, Lea Schönberger, Andreas Lang, Jian-Jia Chen, Peter Marwedel:
Can Flexible Multi-Core Scheduling Help to Execute Machine Learning Algorithms Resource-Efficiently? SCOPES 2019: 59-62 - 2018
- [b1]Helena Kotthaus:
Methods for efficient resource utilization in statistical machine learning algorithms. Technical University of Dortmund, Germany, 2018 - 2017
- [c5]Helena Kotthaus, Jakob Richter, Andreas Lang, Janek Thomas, Bernd Bischl, Peter Marwedel, Jörg Rahnenführer, Michel Lang:
RAMBO: Resource-Aware Model-Based Optimization with Scheduling for Heterogeneous Runtimes and a Comparison with Asynchronous Model-Based Optimization. LION 2017: 180-195 - 2016
- [c4]Jakob Richter, Helena Kotthaus, Bernd Bischl, Peter Marwedel, Jörg Rahnenführer, Michel Lang:
Faster Model-Based Optimization Through Resource-Aware Scheduling Strategies. LION 2016: 267-273 - [c3]Ingo Korb, Helena Kotthaus, Peter Marwedel:
mmapcopy: efficient memory footprint reduction using application knowledge. SAC 2016: 1832-1837 - 2014
- [c2]Helena Kotthaus, Ingo Korb, Michael Engel, Peter Marwedel:
Dynamic page sharing optimization for the R language. DLS 2014: 79-90 - 2011
- [c1]Heiko Falk, Helena Kotthaus:
WCET-driven cache-aware code positioning. CASES 2011: 145-154
Coauthor Index
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