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84 Publications


2021 | Conference Paper | LibreCat-ID: 28350
Sharma, Arnab, et al. “MLCHECK–Property-Driven Testing of Machine Learning Classifiers.” Proceedings of the 20th IEEE International Conference on Machine Learning and Applications (ICMLA), IEEE.
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2021 | Journal Article | LibreCat-ID: 21004
Wever, Marcel Dominik, et al. “AutoML for Multi-Label Classification: Overview and Empirical Evaluation.” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, pp. 1–1, doi:10.1109/tpami.2021.3051276.
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2021 | Journal Article | LibreCat-ID: 21092
Mohr, Felix, et al. “Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning.” IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE.
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2021 | Conference Paper | LibreCat-ID: 21570
Tornede, Tanja, et al. “Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance.” Proceedings of the Genetic and Evolutionary Computation Conference, 2021.
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2021 | Conference Paper | LibreCat-ID: 22913
Hüllermeier, Eyke, et al. Automated Machine Learning, Bounded Rationality, and Rational Metareasoning. 2021.
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2021 | Preprint | LibreCat-ID: 30866
Tornede, Tanja, et al. “Towards Green Automated Machine Learning: Status Quo and Future Directions.” ArXiv:2111.05850, 2021.
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2021 | Dissertation | LibreCat-ID: 27284 | OA
Wever, Marcel Dominik. Automated Machine Learning for Multi-Label Classification. 2021, doi:10.17619/UNIPB/1-1302.
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2021 | Conference Paper | LibreCat-ID: 21198
Hanselle, Jonas Manuel, et al. Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data. 2021.
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2020 | Conference Paper | LibreCat-ID: 17407
Tornede, Alexander, et al. “Extreme Algorithm Selection with Dyadic Feature Representation.” Discovery Science, 2020.
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2020 | Conference Paper | LibreCat-ID: 17408
Hanselle, Jonas Manuel, et al. “Hybrid Ranking and Regression for Algorithm Selection.” KI 2020: Advances in Artificial Intelligence, 2020.
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2020 | Conference Paper | LibreCat-ID: 17424
Tornede, Tanja, et al. “AutoML for Predictive Maintenance: One Tool to RUL Them All.” Proceedings of the ECMLPKDD 2020, 2020, doi:10.1007/978-3-030-66770-2_8.
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2020 | Conference Paper | LibreCat-ID: 20306
Tornede, Alexander, et al. “Towards Meta-Algorithm Selection.” Workshop MetaLearn 2020 @ NeurIPS 2020, 2020.
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2020 | Conference Paper | LibreCat-ID: 18276
Tornede, Alexander, et al. “Run2Survive: A Decision-Theoretic Approach to Algorithm Selection Based on Survival Analysis.” ACML 2020, 2020.
LibreCat | Download (ext.)
 

2020 | Conference Paper | LibreCat-ID: 15629
Wever, Marcel Dominik, et al. LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification. Springer.
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2020 | Journal Article | LibreCat-ID: 15025
Wever, Marcel Dominik, et al. “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets.” Evolutionary Computation, vol. 28, no. 2, MIT Press Journals, 2020, pp. 165–193, doi:10.1162/evco_a_00266.
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2020 | Dissertation | LibreCat-ID: 16935
Moussalem, Diego Campos. Knowledge Graphs for Multilingual Language Translation and Generation. 2020, doi:10.17619/UNIPB/1-980.
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2020 | Journal Article | LibreCat-ID: 13770
Karl, Holger, et al. “A Case for a New IT Ecosystem: On-The-Fly Computing.” Business & Information Systems Engineering, vol. 62, no. 6, Springer, 2020, pp. 467–81, doi:10.1007/s12599-019-00627-x.
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2019 | Conference Abstract | LibreCat-ID: 8868
Wever, Marcel Dominik, et al. Towards Automated Machine Learning for Multi-Label Classification. 2019.
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2019 | Conference Paper | LibreCat-ID: 15007 | OA
Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA.” Proceedings ACML, Asian Conference on Machine Learning (Proceedings of Machine Learning Research, 101), 2019, doi:10.1016/j.jmva.2019.02.017.
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2019 | Conference Paper | LibreCat-ID: 15011 | OA
Tornede, Alexander, et al. “Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking.” Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019, edited by Frank Hoffmann et al., KIT Scientific Publishing, Karlsruhe, 2019, pp. 135–46.
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