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10 Publications
2024 | Journal Article | LibreCat-ID: 54548
Prager, Raphael Patrick, and Heike Trautmann. “Exploratory Landscape Analysis for Mixed-Variable Problems.” IEEE Transactions on Evolutionary Computation, 2024, 1–1. https://doi.org/10.1109/TEVC.2024.3399560.
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2024 | Conference Paper | LibreCat-ID: 56277
Kilsbach, Sebastian, and Nadine Michel. “Computer-Based Generation of Learner-Sensitive Feedback to Argumentative Learner Texts.” 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
Nachtigall, Marcus, Michael Schlichtig, and Eric Bodden. “Evaluation of Usability Criteria Addressed by Static Analysis Tools on a Large Scale.” In Software Engineering 2023, 95–96. Bonn: Gesellschaft für Informatik e.V., 2023.
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2023 | Conference Paper | LibreCat-ID: 52816
Gräßler, Iris, and Michael Hieb. “Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing.” In Lectures, 253–524. AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany, 2023. https://doi.org/10.5162/smsi2023/d7.4.
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2022 | Conference Paper | LibreCat-ID: 32410
Nachtigall, Marcus, Michael Schlichtig, and Eric Bodden. “A Large-Scale Study of Usability Criteria Addressed by Static Analysis Tools.” In Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis, 532–43. ACM, 2022. https://doi.org/10.1145/3533767.
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2021 | Journal Article | LibreCat-ID: 21004
Wever, Marcel Dominik, Alexander Tornede, Felix Mohr, and Eyke Hüllermeier. “AutoML for Multi-Label Classification: Overview and Empirical Evaluation.” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 1–1. https://doi.org/10.1109/tpami.2021.3051276.
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2021 | Book Chapter | LibreCat-ID: 48881
Heins, Jonathan, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, and Pascal Kerschke. “On the Potential of Normalized TSP Features for Automated Algorithm Selection.” In Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 1–15. New York, NY, USA: Association for Computing Machinery, 2021.
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2020 | Conference Paper | LibreCat-ID: 48897
Seiler, Moritz, Janina Pohl, Jakob Bossek, Pascal Kerschke, and Heike Trautmann. “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.” In Parallel Problem Solving from {Nature} (PPSN XVI), 48–64. Berlin, Heidelberg: Springer-Verlag, 2020. https://doi.org/10.1007/978-3-030-58112-1_4.
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2018 | Conference Paper | LibreCat-ID: 3852 | 
Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “ML-Plan for Unlimited-Length Machine Learning Pipelines.” In ICML 2018 AutoML Workshop, 2018.
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2018 | Journal Article | LibreCat-ID: 48884
Kerschke, Pascal, Lars Kotthoff, Jakob Bossek, Holger H. Hoos, and Heike Trautmann. “Leveraging TSP Solver Complementarity through Machine Learning.” Evolutionary Computation 26, no. 4 (2018): 597–620. https://doi.org/10.1162/evco_a_00215.
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