| AutoML for Multi-Label Classification: Overview and Empirical Evaluation M Wever, A Tornede, F Mohr, E Hüllermeier IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 | 35 | 2021 |
| Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning F Mohr, M Wever, A Tornede, E Hüllermeier IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 | 20 | 2021 |
| Extreme Algorithm Selection with Dyadic Feature Representation A Tornede, M Wever, E Hüllermeier Discovery Science 2020, 309--324, 2020 | 16 | 2020 |
| AutoML for Predictive Maintenance: One Tool to RUL them all T Tornede, A Tornede, M Wever, F Mohr, E Hüllermeier IoTStream @ ECMLPKDD 2020, 2020 | 15 | 2020 |
| Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis A Tornede, M Wever, S Werner, F Mohr, E Hüllermeier 12th Asian Conference on Machine Learning (ACML), 2020, 2020 | 13 | 2020 |
| Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance T Tornede, A Tornede, M Wever, E Hüllermeier Proceedings of the Genetic and Evolutionary Computation Conference, 2021 | 10 | 2021 |
| Hybrid Ranking and Regression for Algorithm Selection J Hanselle, A Tornede, M Wever, E Hüllermeier 43rd German Conference on Artificial Intelligence (KI 2020), 2020 | 10 | 2020 |
| Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking A Tornede, M Wever, E Hüllermeier 29th Workshop Computational Intelligence, November 2019, 2019 | 10 | 2019 |
| Towards Green Automated Machine Learning: Status Quo and Future Directions T Tornede, A Tornede, J Hanselle, M Wever, F Mohr, E Hüllermeier arXiv preprint arXiv:2111.05850, 2021 | 9 | 2021 |
| Algorithm selection on a meta level A Tornede, L Gehring, T Tornede, M Wever, E Hüllermeier Machine Learning, 2022 | 8 | 2022 |
| Automating Multi-Label Classification Extending ML-Plan M Wever, F Mohr, A Tornede, E Hüllermeier 6th ICML Workshop on Automated Machine Learning, 2019 | 8 | 2019 |
| A Survey of Methods for Automated Algorithm Configuration E Schede, J Brandt, A Tornede, M Wever, V Bengs, E Hüllermeier, ... Journal of Artificial Intelligence, 2022 | 7 | 2022 |
| Towards Meta-Algorithm Selection A Tornede, M Wever, E Hüllermeier Workshop on Meta-Learning (MetaLearn 2020) @ NeurIPS 2020, 2020 | 6 | 2020 |
| LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification M Wever, A Tornede, F Mohr, E Hüllermeier Symposium on Intelligent Data Analysis, 2020, 2020 | 5 | 2020 |
| Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data J Hanselle, A Tornede, M Wever, E Hüllermeier The 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining …, 2021 | 4 | 2021 |
| HARRIS: Hybrid Ranking and Regression Forests for Algorithm Selection L Fehring, J Hanselle, A Tornede Workshop on Meta-Learning (MetaLearn 2022) @ NeurIPS 2022, 2022 | 1 | 2022 |
| Machine Learning for Online Algorithm Selection under Censored Feedback A Tornede, V Bengs, E Hüllermeier Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI …, 2022 | 1 | 2022 |
| Automated Machine Learning, Bounded Rationality, and Rational Metareasoning E Hüllermeier, F Mohr, A Tornede, M Wever ECMLPKDD Workshop on Automating Data Science (ADS2021), 2021 | 1 | 2021 |
| From Automated to On-The-Fly Machine Learning F Mohr, M Wever, A Tornede, E Hüllermeier INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik–Informatik für …, 2019 | 1 | 2019 |
| jPL: A Java-based Software Framework for Preference Learning P Gupta, A Hetzer, T Tornede, S Gottschalk, A Kornelsen, S Osterbrink, ... | 1 | 2017 |
Eyke HüllermeierProfessor of Computer Science, Paderborn UniversityVerified email at upb.de
