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448 Publications


2021 | Journal Article | LibreCat-ID: 21535
Bengs V, Busa-Fekete R, El Mesaoudi-Paul A, Hüllermeier E. Preference-based Online Learning with Dueling Bandits: A Survey. Journal of Machine Learning Research. 2021;22(7):1-108.
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2021 | Preprint | LibreCat-ID: 21600
Dellnitz M, Hüllermeier E, Lücke M, et al. Efficient time stepping for numerical integration using reinforcement  learning. arXiv:210403562. 2021.
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2021 | Conference Paper | LibreCat-ID: 24382
Gevers K, Schöppner V, Hüllermeier E. Heated tool butt welding of two different materials –  Established methods versus artificial intelligence. In: ; 2021.
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2021 | Journal Article | LibreCat-ID: 21004
Wever MD, Tornede A, Mohr F, Hüllermeier E. AutoML for Multi-Label Classification: Overview and Empirical Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence. Published online 2021:1-1. doi:10.1109/tpami.2021.3051276
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2021 | Journal Article | LibreCat-ID: 21092
Mohr F, Wever MD, Tornede A, Hüllermeier E. Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence.
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2021 | Conference Paper | LibreCat-ID: 21198
Hanselle JM, Tornede A, Wever MD, Hüllermeier E. Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data. In: ; 2021.
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2021 | Conference Paper | LibreCat-ID: 22913
Hüllermeier E, Mohr F, Tornede A, Wever MD. Automated Machine Learning, Bounded Rationality, and Rational Metareasoning. In: ; 2021.
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2021 | Conference Paper | LibreCat-ID: 27381
Damke C, Hüllermeier E. Ranking Structured Objects with Graph Neural Networks. In: Soares C, Torgo L, eds. Proceedings of The 24th International Conference on Discovery Science (DS 2021). Vol 12986. Lecture Notes in Computer Science. Springer; 2021:166-180. doi:10.1007/978-3-030-88942-5
LibreCat | DOI | arXiv
 

2021 | Conference Paper | LibreCat-ID: 22914
Mohr F, Wever MD. Replacing the Ex-Def Baseline in AutoML by Naive AutoML. In: ; 2021.
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2021 | Conference Paper | LibreCat-ID: 21570
Tornede T, Tornede A, Wever MD, Hüllermeier E. Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance. In: Proceedings of the Genetic and Evolutionary Computation Conference. ; 2021.
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2021 | Conference Paper | LibreCat-ID: 23779
Bernijazov R, Dicks A, Dumitrescu R, et al. A Meta-Review on Artificial Intelligence in Product Creation. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21). ; 2021.
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2021 | Dissertation | LibreCat-ID: 27284
Wever MD. Automated Machine Learning for Multi-Label Classification.; 2021.
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2020 | Conference Paper | LibreCat-ID: 19953
Damke C, Melnikov V, Hüllermeier E. A Novel Higher-order Weisfeiler-Lehman Graph Convolution. In: Jialin Pan S, Sugiyama M, eds. Proceedings of the 12th Asian Conference on Machine Learning (ACML 2020). Vol 129. Proceedings of Machine Learning Research. Bangkok, Thailand: PMLR; 2020:49-64.
LibreCat | Files available | arXiv
 

2020 | Conference Paper | LibreCat-ID: 17407
Tornede A, Wever MD, Hüllermeier E. Extreme Algorithm Selection with Dyadic Feature Representation. In: Discovery Science. ; 2020.
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2020 | Book Chapter | LibreCat-ID: 18014
El Mesaoudi-Paul A, Weiß D, Bengs V, Hüllermeier E, Tierney K. Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach. In: Learning and Intelligent Optimization. LION 2020. Vol 12096. Lecture Notes in Computer Science. Cham: Springer; 2020:216-232. doi:10.1007/978-3-030-53552-0_22
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2020 | Preprint | LibreCat-ID: 21536
Bengs V, Hüllermeier E. Multi-Armed Bandits with Censored Consumption of Resources. arXiv:201100813. 2020.
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2020 | Preprint | LibreCat-ID: 17605
Heid SH, Wever MD, Hüllermeier E. Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction. Journal of Data Mining and Digital Humanities.
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2020 | Conference Paper | LibreCat-ID: 17408
Hanselle JM, Tornede A, Wever MD, Hüllermeier E. Hybrid Ranking and Regression for Algorithm Selection. In: KI 2020: Advances in Artificial Intelligence. ; 2020.
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2020 | Conference Paper | LibreCat-ID: 15629
Wever MD, Tornede A, Mohr F, Hüllermeier E. LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification. In: Springer.
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2020 | Conference Paper | LibreCat-ID: 20306
Tornede A, Wever MD, Hüllermeier E. Towards Meta-Algorithm Selection. In: Workshop MetaLearn 2020 @ NeurIPS 2020. ; 2020.
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2020 | Book Chapter | LibreCat-ID: 19521
Pfannschmidt K, Hüllermeier E. Learning Choice Functions via Pareto-Embeddings. In: Lecture Notes in Computer Science. Cham; 2020. doi:10.1007/978-3-030-58285-2_30
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2020 | Conference Paper | LibreCat-ID: 17424
Tornede T, Tornede A, Wever MD, Mohr F, Hüllermeier E. AutoML for Predictive Maintenance: One Tool to RUL Them All. In: Proceedings of the ECMLPKDD 2020. ; 2020. doi:10.1007/978-3-030-66770-2_8
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2020 | Journal Article | LibreCat-ID: 16725
Richter C, Hüllermeier E, Jakobs M-C, Wehrheim H. Algorithm Selection for Software Validation Based on Graph Kernels. Journal of Automated Software Engineering.
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2020 | Preprint | LibreCat-ID: 18017
El Mesaoudi-Paul A, Bengs V, Hüllermeier E. Online Preselection with Context Information under the Plackett-Luce  Model. arXiv:200204275.
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2020 | Conference Paper | LibreCat-ID: 21534
Bengs V, Hüllermeier E. Preselection Bandits. In: International Conference on Machine Learning. ; 2020:778-787.
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2020 | Conference Paper | LibreCat-ID: 18276
Tornede A, Wever MD, Werner S, Mohr F, Hüllermeier E. Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis. In: ACML 2020. ; 2020.
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2020 | Journal Article | LibreCat-ID: 15025
Wever MD, van Rooijen L, Hamann H. Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets. Evolutionary Computation. 2020;28(2):165–193. doi:10.1162/evco_a_00266
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2019 | Journal Article | LibreCat-ID: 14028
Bengs V, Holzmann H. Adaptive confidence sets for kink estimation. Electronic Journal of Statistics. 2019:1523-1579. doi:10.1214/19-ejs1555
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2019 | Journal Article | LibreCat-ID: 15002
Waegeman W, Dembczynski K, Hüllermeier E. Multi-target prediction: a unifying view on problems and methods. Data Mining and Knowledge Discovery. 2019;33(2):293-324. doi:10.1007/s10618-018-0595-5
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2019 | Conference Paper | LibreCat-ID: 15014
Hüllermeier E, Couso I, Diestercke S. Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants. In: Proceedings SUM 2019, International Conference on Scalable Uncertainty Management. ; 2019.
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2019 | Conference Paper | LibreCat-ID: 15007
Melnikov V, Hüllermeier E. Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA. In: 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 | Preprint | LibreCat-ID: 18018
Bengs V, Holzmann H. Uniform approximation in classical weak convergence theory. arXiv:190309864. 2019.
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2019 | Preprint | LibreCat-ID: 19523
Pfannschmidt K, Gupta P, Hüllermeier E. Learning Choice Functions: Concepts and Architectures. arXiv:190110860. 2019.
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2019 | Journal Article | LibreCat-ID: 17565
Merten M-L, Seemann N, Wever MD. Grammatikwandel digital-kulturwissenschaftlich erforscht. Mittelniederdeutscher Sprachausbau im interdisziplinären Zugriff. Niederdeutsches Jahrbuch. 2019;(142):124-146.
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2019 | Conference Paper | LibreCat-ID: 15003
Mortier T, Wydmuch M, Dembczynski K, Hüllermeier E, Waegeman W. Set-Valued Prediction in Multi-Class Classification. In: Proceedings of the 31st Benelux Conference on Artificial Intelligence {(BNAIC} 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), Brussels, Belgium, November 6-8, 2019. ; 2019.
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2019 | Journal Article | LibreCat-ID: 15015
Henzgen S, Hüllermeier E. Mining Rank Data. ACM Transactions on Knowledge Discovery from Data. 2019:1-36. doi:10.1145/3363572
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2019 | Conference Paper | LibreCat-ID: 10232
Wever MD, Mohr F, Tornede A, Hüllermeier E. Automating Multi-Label Classification Extending ML-Plan. In: ; 2019.
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2019 | Journal Article | LibreCat-ID: 10578
Tagne VK, Fotso S, Fono LA, Hüllermeier E. Choice Functions Generated by Mallows and Plackett–Luce Relations. New Mathematics and Natural Computation. 2019;15(2):191-213.
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2019 | Book Chapter | LibreCat-ID: 15004
Ahmadi Fahandar M, Hüllermeier E. Feature Selection for Analogy-Based Learning to Rank. In: Discovery Science. Cham; 2019. doi:10.1007/978-3-030-33778-0_22
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2019 | Conference Paper | LibreCat-ID: 15009
Epple N, Dari S, Drees L, Protschky V, Riener A. Influence of Cruise Control on Driver Guidance - a Comparison between System Generations and Countries. In: 2019 IEEE Intelligent Vehicles Symposium (IV). ; 2019. doi:10.1109/ivs.2019.8814100
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2019 | Conference Paper | LibreCat-ID: 15011
Tornede A, Wever MD, Hüllermeier E. Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking. In: Hoffmann F, Hüllermeier E, Mikut R, eds. Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019. KIT Scientific Publishing, Karlsruhe; 2019:135-146.
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2019 | Book Chapter | LibreCat-ID: 15005
Ahmadi Fahandar M, Hüllermeier E. Analogy-Based Preference Learning with Kernels. In: KI 2019: Advances in Artificial Intelligence. Cham; 2019. doi:10.1007/978-3-030-30179-8_3
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2019 | Conference Abstract | LibreCat-ID: 13132
Mohr F, Wever MD, Tornede A, Hüllermeier E. From Automated to On-The-Fly Machine Learning. In: INFORMATIK 2019: 50 Jahre Gesellschaft Für Informatik – Informatik Für Gesellschaft. INFORMATIK 2019, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik. Bonn: Gesellschaft für Informatik e.V.; 2019:273-274.
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2019 | Journal Article | LibreCat-ID: 14027
Bengs V, Eulert M, Holzmann H. Asymptotic confidence sets for the jump curve in bivariate regression problems. Journal of Multivariate Analysis. 2019:291-312. doi:10.1016/j.jmva.2019.02.017
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2019 | Journal Article | LibreCat-ID: 15001
Couso I, Borgelt C, Hüllermeier E, Kruse R. Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning. IEEE Computational Intelligence Magazine. 2019:31-44. doi:10.1109/mci.2018.2881642
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2019 | Book Chapter | LibreCat-ID: 15006
Nguyen V-L, Destercke S, Hüllermeier E. Epistemic Uncertainty Sampling. In: Discovery Science. Cham; 2019. doi:10.1007/978-3-030-33778-0_7
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2019 | Conference Paper | LibreCat-ID: 15013
Brinker K, Hüllermeier E. A Reduction of Label Ranking to Multiclass Classification. In: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases. Würzburg, Germany; 2019.
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2019 | Conference Abstract | LibreCat-ID: 8868
Wever MD, Mohr F, Hüllermeier E, Hetzer A. Towards Automated Machine Learning for Multi-Label Classification. In: ; 2019.
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2018 | Conference Paper | LibreCat-ID: 10184
Schäfer D, Hüllermeier E. Preference-Based Reinforcement Learning Using Dyad Ranking. In: Proc. 21st Int. Conference on Discovery Science (DS). ; 2018:161-175.
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2018 | Conference Paper | LibreCat-ID: 2479
Mohr F, Wever MD, Hüllermeier E, Faez A. (WIP) Towards the Automated Composition of Machine Learning Services. In: SCC. San Francisco, CA, USA: IEEE; 2018. doi:10.1109/SCC.2018.00039
LibreCat | Files available | DOI | Download (ext.)
 

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