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38 Publications


2019 | Conference Abstract | LibreCat-ID: 8956
Hetzer, Alexander, et al. Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking. 2019.
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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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2018 | Conference Paper | LibreCat-ID: 2479
Mohr, Felix, et al. “(WIP) Towards the Automated Composition of Machine Learning Services.” SCC, IEEE, 2018, doi:10.1109/SCC.2018.00039.
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2018 | Conference Paper | LibreCat-ID: 3852
Wever, Marcel Dominik, et al. “ML-Plan for Unlimited-Length Machine Learning Pipelines.” ICML 2018 AutoML Workshop, 2018.
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2018 | Bachelorsthesis | LibreCat-ID: 5936
Scheibl, Manuel. Learning about Learning Curves from Dataset Properties. 2018.
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2018 | Conference Paper | LibreCat-ID: 2471
Mohr, Felix, et al. “On-The-Fly Service Construction with Prototypes.” SCC, IEEE Computer Society, 2018, doi:10.1109/SCC.2018.00036.
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2018 | Book Chapter | LibreCat-ID: 6423
Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning Using Dyad Ranking.” Discovery Science, Springer International Publishing, 2018, pp. 161–75, doi:10.1007/978-3-030-01771-2_11.
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2018 | Conference Paper | LibreCat-ID: 2109
Wever, Marcel Dominik, et al. “Ensembles of Evolved Nested Dichotomies for Classification.” Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018, ACM, 2018, doi:10.1145/3205455.3205562.
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2018 | Conference Paper | LibreCat-ID: 3552
Mohr, Felix, et al. “Reduction Stumps for Multi-Class Classification.” Proceedings of the Symposium on Intelligent Data Analysis, doi:10.1007/978-3-030-01768-2_19.
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2018 | Conference Paper | LibreCat-ID: 2857
Mohr, Felix, et al. “Programmatic Task Network Planning.” Proceedings of the 28th International Conference on Automated Planning and Scheduling, AAAI, 2018.
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2018 | Journal Article | LibreCat-ID: 3402
Melnikov, Vitalik, and Eyke Hüllermeier. “On the Effectiveness of Heuristics for Learning Nested Dichotomies: An Empirical Analysis.” Machine Learning, 2018, doi:10.1007/s10994-018-5733-1.
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2018 | Journal Article | LibreCat-ID: 3510
Mohr, Felix, et al. “ML-Plan: Automated Machine Learning via Hierarchical Planning.” Machine Learning, Springer, 2018, doi:10.1007/s10994-018-5735-z.
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2018 | Conference Abstract | LibreCat-ID: 1379
Seemann, Nina, et al. “Supporting the Cognitive Process in Annotation Tasks.” Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, edited by Kerstin Eckart and Dominik Schlechtweg, 2018.
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2018 | Bachelorsthesis | LibreCat-ID: 5693
Graf, Helena. Ranking of Classification Algorithms in AutoML. 2018.
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2017 | Conference Paper | LibreCat-ID: 1180
Wever, Marcel Dominik, et al. “Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization.” 27th Workshop Computational Intelligence, 2017.
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2017 | Bachelorsthesis | LibreCat-ID: 5694
Schnitker, Nino Noel. Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies. 2017.
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2017 | Conference Abstract | LibreCat-ID: 5722
Gupta, Pritha, et al. JPL: A Java-Based Software Framework for Preference Learning. 2017.
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2017 | Mastersthesis | LibreCat-ID: 5724
Hetzer, Alexander, and Tanja Tornede. Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction. 2017.
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2017 | Conference Paper | LibreCat-ID: 71
Czech, Mike, et al. “Predicting Rankings of Software Verification Tools.” Proceedings of the 3rd International Workshop on Software Analytics, 2017, pp. 23–26, doi:10.1145/3121257.3121262.
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2017 | Conference Paper | LibreCat-ID: 115
Jakobs, Marie-Christine, et al. “Certification Matters for Service Markets.” The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION), edited by Thomas Prinz Marcelo De Barros, Janusz Klink,Tadeus Uhl, 2017, pp. 7–12.
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