| 2026 | AAAI | HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization. | Marcel Wever, Maximilian Muschalik, Fabian Fumagalli, Marius Lindauer |
| 2026 | GECCO | Evolutionary Mapping of Neural Networks to Spatial Accelerators. | Alessandro Pierro, Jason Yik, Jonathan Timcheck, Marius Lindauer, Eyke Hllermeier, Marcel Wever |
| 2025 | GECCO | SynthACticBench: A Capability-Based Synthetic Benchmark for Algorithm Configuration. | Valentin Margraf, Anna Lappe, Marcel Wever, Carolin Benjamins, Eyke Hllermeier, Marius Lindauer |
| 2024 | ICML | Position: Why We Must Rethink Empirical Research in Machine Learning. | Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rgamer, Eyke Hllermeier, Anne-Laure Boulesteix, Bernd Bischl |
| 2024 | IJCAI | Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO. | Jasmin Brandt, Marcel Wever, Viktor Bengs, Eyke Hllermeier |
| 2023 | GECCO | Cooperative Co-Evolution for Ensembles of Nested Dichotomies for Multi-Class Classification. | Marcel Wever, Miran zdogan, Eyke Hllermeier |
| 2023 | IJCAI | A Survey of Methods for Automated Algorithm Configuration (Extended Abstract). | Elias Schede, Jasmin Brandt, Alexander Tornede, Marcel Wever, Viktor Bengs, Eyke Hllermeier, Kevin Tierney |
| 2023 | IDA | Meta-learning for Automated Selection of Anomaly Detectors for Semi-supervised Datasets. | David Schubert, Pritha Gupta, Marcel Wever |
| 2021 | GECCO | Coevolution of remaining useful lifetime estimation pipelines for automated predictive maintenance. | Tanja Tornede, Alexander Tornede, Marcel Wever, Eyke Hllermeier |
| 2021 | PAKDD | Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data. | Jonas Hanselle, Alexander Tornede, Marcel Wever, Eyke Hllermeier |
| 2020 | ACML | Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis. | Alexander Tornede, Marcel Wever, Stefan Werner, Felix Mohr, Eyke Hllermeier |
| 2020 | DIS | Extreme Algorithm Selection with Dyadic Feature Representation. | Alexander Tornede, Marcel Wever, Eyke Hllermeier |
| 2020 | IDA | LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-label Classification. | Marcel Wever, Alexander Tornede, Felix Mohr, Eyke Hllermeier |
| 2020 | KI | Hybrid Ranking and Regression for Algorithm Selection. | Jonas Hanselle, Alexander Tornede, Marcel Wever, Eyke Hllermeier |
| 2019 | GI | From Automated to On-The-Fly Machine Learning. | Felix Mohr, Marcel Wever, Alexander Tornede, Eyke Hllermeier |
| 2018 | GECCO | Ensembles of evolved nested dichotomies for classification. | Marcel Wever, Felix Mohr, Eyke Hllermeier |
| 2018 | IDA | Reduction Stumps for Multi-class Classification. | Felix Mohr, Marcel Wever, Eyke Hllermeier |
| 2017 | GECCO | Active coevolutionary learning of requirements specifications from examples. | Marcel Wever, Lorijn van Rooijen, Heiko Hamann |