Learning decision catalogues for situated decision making: The case of scoring systems
S. Heid, J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, International Journal of Approximate Reasoning 171 (2024).

Learning decision catalogues for situated decision making: The case of scoring systems
S. Heid, J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, International Journal of Approximate Reasoning 171 (2024).

Learning decision catalogues for situated decision making: The case of scoring systems
S. Heid, J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, International Journal of Approximate Reasoning 171 (2024).

Human-AI Co-Construction of Interpretable Predictive Models: The Case of Scoring Systems
S. Heid, J. Kornowicz, J.M. Hanselle, E. Hüllermeier, K. Thommes, in: PROCEEDINGS 34. WORKSHOP COMPUTATIONAL INTELLIGENCE, 2024, p. 233.

Probabilistic Scoring Lists for Interpretable Machine Learning
J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, in: 26th International Conference on Discovery Science , Springer Nature Switzerland, Cham, 2023, pp. 189–203.

Configuration and Evaluation
J.M. Hanselle, E. Hüllermeier, F. Mohr, A.-C. Ngonga Ngomo, M. Sherif, A. Tornede, M.D. Wever, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing – Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 85–104.

Probabilistic Scoring Lists for Interpretable Machine Learning
J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, in: Discovery Science, Springer Nature Switzerland, Cham, 2023.

Configuration and Evaluation
J.M. Hanselle, E. Hüllermeier, F. Mohr, A.-C. Ngonga Ngomo, M. Sherif, A. Tornede, M.D. Wever, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023, pp. 85–104.

Comparing Humans and Algorithms in Feature Ranking: A Case-Study in the Medical Domain
J.M. Hanselle, J. Kornowicz, S. Heid, K. Thommes, E. Hüllermeier, in: M. Leyer, J. Wichmann (Eds.), LWDA’23: Learning, Knowledge, Data, Analysis. , 2023.

HARRIS: Hybrid Ranking and Regression Forests for Algorithm Selection
L. Fehring, J.M. Hanselle, A. Tornede, in: Workshop on Meta-Learning (MetaLearn 2022) @ NeurIPS 2022, 2022.

A Meta-Review on Artiû01cial Intelligence in Product Creation
R. Bernijazov, A. Dicks, R. Dumitrescu, M. Foullois, J.M. Hanselle, E. Hüllermeier, G. Karakaya, P. Ködding, V. Lohweg, M. Malatyali, F. Meyer auf der Heide, M. Panzner, C. Soltenborn, in: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21), 2021.

Towards Green Automated Machine Learning: Status Quo and Future Directions
T. Tornede, A. Tornede, J.M. Hanselle, M.D. Wever, F. Mohr, E. Hüllermeier, ArXiv:2111.05850 (2021).

Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data
J.M. Hanselle, A. Tornede, M.D. Wever, E. Hüllermeier, (2021).

Hybrid Ranking and Regression for Algorithm Selection
J.M. Hanselle, A. Tornede, M.D. Wever, E. Hüllermeier, in: KI 2020: Advances in Artificial Intelligence, 2020.