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Shrub Ensembles for Online Classification


Dec 07, 2021
Sebastian Buschj├Ąger, Sibylle Hess, Katharina Morik

* 9 pages main content, 13 pages appendix, accepted at AAAI-2022 

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There is no Double-Descent in Random Forests


Nov 08, 2021
Sebastian Buschj├Ąger, Katharina Morik

* 11 pages, 3 figures, 3 algorithms 

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Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement


Oct 19, 2021
Sebastian Buschj├Ąger, Katharina Morik

* 2 algorithms, 6 tables, 4 plots and a very long appendix 

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Explaining Deep Learning Representations by Tracing the Training Process


Sep 13, 2021
Lukas Pfahler, Katharina Morik


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Noisy Labels for Weakly Supervised Gamma Hadron Classification


Aug 30, 2021
Lukas Pfahler, Mirko Bunse, Katharina Morik


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The Care Label Concept: A Certification Suite for Trustworthy and Resource-Aware Machine Learning


Jun 01, 2021
Katharina Morik, Helena Kotthaus, Lukas Heppe, Danny Heinrich, Raphael Fischer, Andreas Pauly, Nico Piatkowski


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Providing Meaningful Data Summarizations Using Examplar-based Clustering in Industry 4.0


May 25, 2021
Philipp-Jan Honysz, Alexander Schulze-Struchtrup, Sebastian Buschj├Ąger, Katharina Morik

* arXiv admin note: substantial text overlap with arXiv:2101.08763 

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Yes We Care! -- Certification for Machine Learning Methods through the Care Label Framework


May 21, 2021
Katharina Morik, Helena Kotthaus, Lukas Heppe, Danny Heinrich, Raphael Fischer, Sascha M├╝cke, Andreas Pauly, Matthias Jakobs, Nico Piatkowski


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Bit Error Tolerance Metrics for Binarized Neural Networks


Feb 02, 2021
Sebastian Buschj├Ąger, Jian-Jia Chen, Kuan-Hsun Chen, Mario G├╝nzel, Katharina Morik, Rodion Novkin, Lukas Pfahler, Mikail Yayla

* Presented at DATE Friday Workshop on System-level Design Methods for Deep Learning on Heterogeneous Architectures (SLOHA 2021) (arXiv:2102.00818) 

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GPU-Accelerated Optimizer-Aware Evaluation of Submodular Exemplar Clustering


Jan 21, 2021
Philipp-Jan Honysz, Sebastian Buschj├Ąger, Katharina Morik


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Generalized Negative Correlation Learning for Deep Ensembling


Nov 05, 2020
Sebastian Buschj├Ąger, Lukas Pfahler, Katharina Morik

* 12 pages, 1 figure 

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Very Fast Streaming Submodular Function Maximization


Nov 04, 2020
Sebastian Buschj├Ąger, Philipp-Jan Honysz, Katharina Morik

* 15 pages, 5 figures, 1 table, 8 algorithms 

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Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots


Oct 29, 2020
Nikolaos Nikolaou, Ingo P. Waldmann, Angelos Tsiaras, Mario Morvan, Billy Edwards, Kai Hou Yip, Giovanna Tinetti, Subhajit Sarkar, James M. Dawson, Vadim Borisov, Gjergji Kasneci, Matej Petkovic, Tomaz Stepisnik, Tarek Al-Ubaidi, Rachel Louise Bailey, Michael Granitzer, Sahib Julka, Roman Kern, Patrick Ofner, Stefan Wagner, Lukas Heppe, Mirko Bunse, Katharina Morik

* 20 pages, 7 figures, 2 tables, Submitted to The Astrophysics Journal (ApJ) 

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Resource-Constrained On-Device Learning by Dynamic Averaging


Sep 25, 2020
Lukas Heppe, Michael Kamp, Linara Adilova, Danny Heinrich, Nico Piatkowski, Katharina Morik


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Towards Explainable Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks


Feb 03, 2020
Sebastian Buschj├Ąger, Jian-Jia Chen, Kuan-Hsun Chen, Mario G├╝nzel, Christian Hakert, Katharina Morik, Rodion Novkin, Lukas Pfahler, Mikail Yayla

* 6 pages, 2 figures 

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The Trustworthy Pal: Controlling the False Discovery Rate in Boolean Matrix Factorization


Jul 01, 2019
Sibylle Hess, Nico Piatkowski, Katharina Morik


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The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering


Jul 01, 2019
Sibylle Hess, Wouter Duivesteijn, Philipp Honysz, Katharina Morik


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C-SALT: Mining Class-Specific ALTerations in Boolean Matrix Factorization


Jun 17, 2019
Sibylle Hess, Katharina Morik

* Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, Cham, 2017 

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The PRIMPing Routine -- Tiling through Proximal Alternating Linearized Minimization


Jun 17, 2019
Sibylle Hess, Katharina Morik, Nico Piatkowski

* Data Mining and Knowledge Discovery 31(4): 1090-1131 (2017) 

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Machine Learning meets Data-Driven Journalism: Boosting International Understanding and Transparency in News Coverage


Jun 16, 2016
Elena Erdmann, Karin Boczek, Lars Koppers, Gerret von Nordheim, Christian P├Âlitz, Alejandro Molina, Katharina Morik, Henrik M├╝ller, J├Ârg Rahnenf├╝hrer, Kristian Kersting

* presented at 2016 ICML Workshop on #Data4Good: Machine Learning in Social Good Applications, New York, NY 

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