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10 Publications


2024 | Journal Article | LibreCat-ID: 54548
Exploratory Landscape Analysis for Mixed-Variable Problems
R.P. Prager, H. Trautmann, IEEE Transactions on Evolutionary Computation (2024) 1–1.
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2024 | Conference Paper | LibreCat-ID: 56277
Computer-Based Generation of Learner-Sensitive Feedback to Argumentative Learner Texts
S. Kilsbach, N. Michel, in: Proceedings of the Tenth Conference of the International Society for the Study of Argumentation, 2024.
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2023 | Book Chapter | LibreCat-ID: 52662
Evaluation of Usability Criteria Addressed by Static Analysis Tools on a Large Scale
M. Nachtigall, M. Schlichtig, E. Bodden, in: Software Engineering 2023, Gesellschaft für Informatik e.V., Bonn, 2023, pp. 95–96.
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2023 | Conference Paper | LibreCat-ID: 52816
Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing
I. Gräßler, M. Hieb, in: Lectures, AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany, 2023, pp. 253–524.
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2022 | Conference Paper | LibreCat-ID: 32410
A Large-Scale Study of Usability Criteria Addressed by Static Analysis Tools
M. Nachtigall, M. Schlichtig, E. Bodden, in: Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis, ACM, 2022, pp. 532–543.
LibreCat | Files available | DOI
 

2021 | Journal Article | LibreCat-ID: 21004
AutoML for Multi-Label Classification: Overview and Empirical Evaluation
M.D. Wever, A. Tornede, F. Mohr, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (2021) 1–1.
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2021 | Book Chapter | LibreCat-ID: 48881
On the Potential of Normalized TSP Features for Automated Algorithm Selection
J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, P. Kerschke, in: Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, New York, NY, USA, 2021, pp. 1–15.
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2020 | Conference Paper | LibreCat-ID: 48897
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem
M. Seiler, J. Pohl, J. Bossek, P. Kerschke, H. Trautmann, in: Parallel Problem Solving from {Nature} (PPSN XVI), Springer-Verlag, Berlin, Heidelberg, 2020, pp. 48–64.
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2018 | Conference Paper | LibreCat-ID: 3852 | OA
ML-Plan for Unlimited-Length Machine Learning Pipelines
M.D. Wever, F. Mohr, E. Hüllermeier, in: ICML 2018 AutoML Workshop, 2018.
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2018 | Journal Article | LibreCat-ID: 48884
Leveraging TSP Solver Complementarity through Machine Learning
P. Kerschke, L. Kotthoff, J. Bossek, H.H. Hoos, H. Trautmann, Evolutionary Computation 26 (2018) 597–620.
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