Helena Kotthaus
Helena Kotthaus
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Automatic model selection for high-dimensional survival analysis
M Lang, H Kotthaus, P Marwedel, C Weihs, J Rahnenführer, B Bischl
Journal of Statistical Computation and Simulation 85 (1), 62-76, 2015
WCET-driven cache-aware code positioning
H Falk, H Kotthaus
Proceedings of the 14th international conference on Compilers, architectures …, 2011
Runtime and memory consumption analyses for machine learning R programs
H Kotthaus, I Korb, M Lang, B Bischl, J Rahnenführer, P Marwedel
Journal of Statistical Computation and Simulation 85 (1), 14-29, 2015
Faster model-based optimization through resource-aware scheduling strategies
J Richter, H Kotthaus, B Bischl, P Marwedel, J Rahnenführer, M Lang
Learning and Intelligent Optimization: 10th International Conference, LION …, 2016
Dynamic page sharing optimization for the R language
H Kotthaus, I Korb, M Engel, P Marwedel
Proceedings of the 10th ACM Symposium on Dynamic languages, 79-90, 2014
RAMBO: Resource-aware model-based optimization with scheduling for heterogeneous runtimes and a comparison with asynchronous model-based optimization
H Kotthaus, J Richter, A Lang, J Thomas, B Bischl, P Marwedel, ...
Learning and Intelligent Optimization: 11th International Conference, LION …, 2017
Surrogate model-based explainability methods for point cloud nns
H Tan, H Kotthaus
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022
Yes we care!-Certification for machine learning methods through the care label framework
KJ Morik, H Kotthaus, R Fischer, S Mücke, M Jakobs, N Piatkowski, ...
Frontiers in Artificial Intelligence 5, 975029, 2022
Methods for efficient resource utilization in statistical machine learning algorithms
H Kotthaus
Can Flexible Multi-Core Scheduling Help to Execute Machine Learning Algorithms Resource-Efficiently?
H Kotthaus, L Schönberger, A Lang, JJ Chen, P Marwedel
Proceedings of the 22nd International Workshop on Software and Compilers for …, 2019
Scheduling data-intensive tasks on heterogeneous many cores
P Tözün, H Kotthaus
{IEEE} Data Engineering Bulletin 42 (1), 61-72, 2019
Explainability-Aware One Point Attack for Point Cloud Neural Networks
H Tan, H Kotthaus
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023
The care label concept: a certification suite for trustworthy and resource-aware machine learning
K Morik, H Kotthaus, L Heppe, D Heinrich, R Fischer, A Pauly, ...
arXiv preprint arXiv:2106.00512, 2021
Performance analysis for parallel R programs: towards efficient resource utilization
H Kotthaus, I Korb, P Marwedel
Abstract Booklet of the International R User Conference (UseR, 66, 2015
mmapcopy: efficient memory footprint reduction using application knowledge
I Korb, H Kotthaus, P Marwedel
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 1832-1837, 2016
A JVM-based Compiler Strategy for the R Language
H Kotthaus, S Plazar, P Marwedel
Technical report for Collaborative Research Center SFB 876 Providing …, 2012
Performance Analysis for R: Towards a Faster R Interpreter
H Kotthaus, I Korb, M Künne, P Marwedel
Abstract Booklet of the International R User Conference, 2014
Sanc-Screen: Towards a real-world dataset for evaluating explainability methods
M Jakobs, H Kotthaus, I Röder, M Baritz
LWDA, 2022
R goes Mobile: Efficient Scheduling for Parallel R Programs on Heterogeneous Embedded Systems
H Kotthaus, A Lang, O Neugebauer, P Marwedel
The R User Conference, useR! 2017 July 4-7 2017 Brussels, Belgium, 74, 2017
Memory Awareness
H Kotthaus, P Marwedel, M Yayla, S Buschjäger, H Amrouch, KH Chen
Machine Learning under Resource Constraints: Fundamentals, 305-358, 2022
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