| Learning Interpretable Rules for Multi-label Classification E Loza Mencía, J Fürnkranz, E Hüllermeier, M Rapp Explainable and Interpretable Models in Computer Vision and Machine Learning …, 2018 | 6 | 2018 |
| Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules M Rapp, EL Mencía, J Fürnkranz Pacific-Asia Conference on Knowledge Discovery and Data Mining, 29-42, 2018 | 5 | 2018 |
| Learning Gradient Boosted Multi-label Classification Rules M Rapp, EL Mencía, J Fürnkranz, VL Nguyen, E Hüllermeier arXiv preprint arXiv:2006.13346, 2020 | 3 | 2020 |
| Efficient Discovery of Expressive Multi-label Rules Using Relaxed Pruning Y Klein, M Rapp, EL Mencía International Conference on Discovery Science, 367-382, 2019 | 3 | 2019 |
| Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy M Rapp, EL Mencía, J Fürnkranz arXiv preprint arXiv:1911.04393, 2019 | 2 | 2019 |
| On the Trade-Off Between Consistency and Coverage in Multi-label Rule Learning Heuristics M Rapp, EL Mencía, J Fürnkranz International Conference on Discovery Science, 96-111, 2019 | 2 | 2019 |
| Learning Structured Declarative Rule Sets--A Challenge for Deep Discrete Learning J Fürnkranz, E Hüllermeier, EL Mencía, M Rapp arXiv preprint arXiv:2012.04377, 2020 | | 2020 |
| A Flexible Class of Dependence-aware Multi-Label Loss Functions E Hüllermeier, M Wever, EL Mencia, J Fürnkranz, M Rapp arXiv preprint arXiv:2011.00792, 2020 | | 2020 |
| On Aggregation in Ensembles of Multilabel Classifiers VL Nguyen, E Hüllermeier, M Rapp, EL Mencía, J Fürnkranz International Conference on Discovery Science, 533-547, 2020 | | 2020 |
| Rule-Based Multi-label Classification: Challenges and Opportunities E Hüllermeier, J Fürnkranz, EL Mencia, VL Nguyen, M Rapp International Joint Conference on Rules and Reasoning, 3-19, 2020 | | 2020 |
Loza Mencía, EneldoKnowledge Engineering Group, TU DarmstadtVerified email at ke.tu-darmstadt.de
