Hanselle, Jonas Manuel, Eyke Hüllermeier, Felix Mohr, Axel-Cyrille Ngonga Ngomo, Mohamed Sherif, Alexander Tornede, and Marcel Dominik Wever. “Configuration and Evaluation.”https://doi.org/10.5281/zenodo.8068466__In On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, edited by Claus-Jochen Haake, Friedhelm Meyer auf der Heide, Marco Platzner, Henning Wachsmuth, and Heike Wehrheim, 412:85–104. Verlagsschriftenreihe Des Heinz Nixdorf Instituts. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023.https://doi.org/10.5281/zenodo.8068466 .
LibreCat: /record/45884
DOI: 10.5281/zenodo.8068466

Tornede, Alexander. Advanced Algorithm Selection with Machine Learning: Handling Large Algorithm Sets, Learning From Censored Data, and Simplyfing Meta Level Decisions, 2023.https://doi.org/10.17619/UNIPB/1-1780  .
LibreCat: /record/45780
DOI: 10.17619/UNIPB/1-1780 

Schede, Elias, Jasmin Brandt, Alexander Tornede, Marcel Dominik Wever, Viktor Bengs, Eyke Hüllermeier, and Kevin Tierney. “A Survey of Methods for Automated Algorithm Configuration.” ArXiv:2202.01651, 2022.
LibreCat: /record/30868
arXiv: 2202.01651

Fehring, Lukass, Jonas Manuel Hanselle, and Alexander Tornede. “HARRIS: Hybrid Ranking and Regression Forests for Algorithm Selection.” In Workshop on Meta-Learning (MetaLearn 2022) @ NeurIPS 2022, 2022.
LibreCat: /record/34103
arXiv: 2210.17341

Tornede, Alexander, Viktor Bengs, and Eyke Hüllermeier. “Machine Learning for Online Algorithm Selection under Censored Feedback.” Proceedings of the 36th AAAI Conference on Artificial Intelligence. AAAI, 2022.
LibreCat: /record/30867
arXiv: 2109.06234

Tornede, Alexander, Lukas Gehring, Tanja Tornede, Marcel Dominik Wever, and Eyke Hüllermeier. “Algorithm Selection on a Meta Level.” Machine Learning, 2022.
LibreCat: /record/30865
arXiv: 2107.09414

Gevers, Karina, Alexander Tornede, Marcel Dominik Wever, Volker Schöppner, and Eyke Hüllermeier. “A Comparison of Heuristic, Statistical, and Machine Learning Methods for Heated Tool Butt Welding of Two Different Materials.”https://doi.org/10.1007/s40194-022-01339-9__Welding in the World, 2022.https://doi.org/10.1007/s40194-022-01339-9 .
LibreCat: /record/33090
DOI: 10.1007/s40194-022-01339-9

Wever, Marcel Dominik, Alexander Tornede, Felix Mohr, and Eyke Hüllermeier. “AutoML for Multi-Label Classification: Overview and Empirical Evaluation.”https://doi.org/10.1109/tpami.2021.3051276__IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 1–1.https://doi.org/10.1109/tpami.2021.3051276 .
LibreCat: /record/21004
DOI: 10.1109/tpami.2021.3051276

Mohr, Felix, Marcel Dominik Wever, Alexander Tornede, and Eyke Hüllermeier. “Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning.” IEEE Transactions on Pattern Analysis and Machine Intelligence, n.d.
LibreCat: /record/21092

Tornede, Tanja, Alexander Tornede, Marcel Dominik Wever, and Eyke Hüllermeier. “Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance.” In Proceedings of the Genetic and Evolutionary Computation Conference, 2021.
LibreCat: /record/21570

Hüllermeier, Eyke, Felix Mohr, Alexander Tornede, and Marcel Dominik Wever. “Automated Machine Learning, Bounded Rationality, and Rational Metareasoning,” 2021.
LibreCat: /record/22913

Tornede, Tanja, Alexander Tornede, Jonas Manuel Hanselle, Marcel Dominik Wever, Felix Mohr, and Eyke Hüllermeier. “Towards Green Automated Machine Learning: Status Quo and Future Directions.” ArXiv:2111.05850, 2021.
LibreCat: /record/30866
arXiv: 2111.05850

Hanselle, Jonas Manuel, Alexander Tornede, Marcel Dominik Wever, and Eyke Hüllermeier. “Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data.” PAKDD, 2021.
LibreCat: /record/21198

Tornede, Alexander, Marcel Dominik Wever, and Eyke Hüllermeier. “Extreme Algorithm Selection with Dyadic Feature Representation.” In Discovery Science, 2020.
LibreCat: /record/17407

Hanselle, Jonas Manuel, Alexander Tornede, Marcel Dominik Wever, and Eyke Hüllermeier. “Hybrid Ranking and Regression for Algorithm Selection.” In KI 2020: Advances in Artificial Intelligence, 2020.
LibreCat: /record/17408

Tornede, Tanja, Alexander Tornede, Marcel Dominik Wever, Felix Mohr, and Eyke Hüllermeier. “AutoML for Predictive Maintenance: One Tool to RUL Them All.”https://doi.org/10.1007/978-3-030-66770-2_8__In Proceedings of the ECMLPKDD 2020, 2020.https://doi.org/10.1007/978-3-030-66770-2_8 .
LibreCat: /record/17424
DOI: 10.1007/978-3-030-66770-2_8

Tornede, Alexander, Marcel Dominik Wever, and Eyke Hüllermeier. “Towards Meta-Algorithm Selection.” In Workshop MetaLearn 2020 @ NeurIPS 2020, 2020.
LibreCat: /record/20306

Tornede, Alexander, Marcel Dominik Wever, Stefan Werner, Felix Mohr, and Eyke Hüllermeier. “Run2Survive: A Decision-Theoretic Approach to Algorithm Selection Based on Survival Analysis.” In ACML 2020, 2020.
LibreCat: /record/18276

Wever, Marcel Dominik, Alexander Tornede, Felix Mohr, and Eyke Hüllermeier. “LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification.” Springer, n.d.
LibreCat: /record/15629

Wever, Marcel Dominik, Felix Mohr, Eyke Hüllermeier, and Alexander Hetzer. “Towards Automated Machine Learning for Multi-Label Classification,” 2019.
LibreCat: /record/8868