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14 Publications


2024 | Journal Article | LibreCat-ID: 54911
S. Heid, J. M. Hanselle, J. Fürnkranz, and E. Hüllermeier, “Learning decision catalogues for situated decision making: The case of scoring systems,” International Journal of Approximate Reasoning, vol. 171, Art. no. 109190, 2024, doi: 10.1016/j.ijar.2024.109190.
LibreCat | DOI
 

2024 | Journal Article | LibreCat-ID: 54910
S. Heid, J. M. Hanselle, J. Fürnkranz, and E. Hüllermeier, “Learning decision catalogues for situated decision making: The case of scoring systems,” International Journal of Approximate Reasoning, vol. 171, Art. no. 109190, 2024, doi: 10.1016/j.ijar.2024.109190.
LibreCat | DOI
 

2024 | Journal Article | LibreCat-ID: 54907
S. Heid, J. M. Hanselle, J. Fürnkranz, and E. Hüllermeier, “Learning decision catalogues for situated decision making: The case of scoring systems,” International Journal of Approximate Reasoning, vol. 171, Art. no. 109190, 2024, doi: 10.1016/j.ijar.2024.109190.
LibreCat | DOI
 

2024 | Conference Paper | LibreCat-ID: 57645
S. Heid, J. Kornowicz, J. M. Hanselle, E. Hüllermeier, and K. Thommes, “Human-AI Co-Construction of Interpretable Predictive Models: The Case of Scoring Systems,” in PROCEEDINGS 34. WORKSHOP COMPUTATIONAL INTELLIGENCE, 2024, vol. 21, p. 233.
LibreCat
 

2023 | Conference Paper | LibreCat-ID: 51373
J. M. Hanselle, J. Fürnkranz, and E. Hüllermeier, “Probabilistic Scoring Lists for Interpretable Machine Learning,” in 26th International Conference on Discovery Science , Porto, 2023, vol. 14050, pp. 189–203, doi: 10.1007/978-3-031-45275-8_13.
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2023 | Book Chapter | LibreCat-ID: 54613
J. M. Hanselle et al., “Configuration and Evaluation,” in On-The-Fly Computing – Individualized IT-services in dynamic markets, vol. 412, C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, Eds. Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 85–104.
LibreCat | DOI
 

2023 | Book Chapter | LibreCat-ID: 54909
J. M. Hanselle, J. Fürnkranz, and E. Hüllermeier, “Probabilistic Scoring Lists for Interpretable Machine Learning,” in Discovery Science, Cham: Springer Nature Switzerland, 2023.
LibreCat | DOI
 

2023 | Book Chapter | LibreCat-ID: 45884 | OA
J. M. Hanselle et al., “Configuration and Evaluation,” in On-The-Fly Computing -- Individualized IT-services in dynamic markets, vol. 412, C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, Eds. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 85–104.
LibreCat | Files available | DOI
 

2023 | Conference Paper | LibreCat-ID: 51209
J. M. Hanselle, J. Kornowicz, S. Heid, K. Thommes, and E. Hüllermeier, “Comparing Humans and Algorithms in Feature Ranking: A Case-Study in the Medical Domain,” in LWDA’23: Learning, Knowledge, Data, Analysis. , 2023.
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2022 | Conference Paper | LibreCat-ID: 34103
L. Fehring, J. M. Hanselle, and A. Tornede, “HARRIS: Hybrid Ranking and Regression Forests for Algorithm Selection,” presented at the Workshop on Meta-Learning (MetaLearn 2022) @ NeurIPS 2022, Baltimore, 2022.
LibreCat | arXiv
 

2021 | Conference Paper | LibreCat-ID: 23779
R. Bernijazov et al., “A Meta-Review on Artificial Intelligence in Product Creation,” presented at the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021) - Workshop “AI and Product Design,” Montreal, Kanada, 2021.
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2021 | Preprint | LibreCat-ID: 30866
T. Tornede, A. Tornede, J. M. Hanselle, M. D. Wever, F. Mohr, and E. Hüllermeier, “Towards Green Automated Machine Learning: Status Quo and Future Directions,” arXiv:2111.05850. 2021.
LibreCat | arXiv
 

2021 | Conference Paper | LibreCat-ID: 21198
J. M. Hanselle, A. Tornede, M. D. Wever, and E. Hüllermeier, “Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data.” 2021.
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2020 | Conference Paper | LibreCat-ID: 17408
J. M. Hanselle, A. Tornede, M. D. Wever, and E. Hüllermeier, “Hybrid Ranking and Regression for Algorithm Selection,” presented at the 43rd German Conference on Artificial Intelligence, 2020.
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