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25 Publications


2023 | Book Chapter | LibreCat-ID: 45884 | OA
Hanselle, Jonas Manuel, et al. “Configuration and Evaluation.” On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, edited by Claus-Jochen Haake et al., vol. 412, Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 85–104, doi:10.5281/zenodo.8068466.
LibreCat | Files available | DOI
 

2023 | Dissertation | LibreCat-ID: 45780 | OA
Tornede, Alexander. Advanced Algorithm Selection with Machine Learning: Handling Large Algorithm Sets, Learning From Censored Data, and Simplyfing Meta Level Decisions. 2023, doi:10.17619/UNIPB/1-1780 .
LibreCat | Files available | DOI
 

2022 | Preprint | LibreCat-ID: 30868
Schede, Elias, et al. “A Survey of Methods for Automated Algorithm Configuration.” ArXiv:2202.01651, 2022.
LibreCat | arXiv
 

2022 | Conference Paper | LibreCat-ID: 34103
Fehring, Lukass, et al. “HARRIS: Hybrid Ranking and Regression Forests for Algorithm Selection.” Workshop on Meta-Learning (MetaLearn 2022) @ NeurIPS 2022, 2022.
LibreCat | arXiv
 

2022 | Preprint | LibreCat-ID: 30867
Tornede, Alexander, et al. “Machine Learning for Online Algorithm Selection under Censored Feedback.” Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI, 2022.
LibreCat | arXiv
 

2022 | Preprint | LibreCat-ID: 30865
Tornede, Alexander, et al. “Algorithm Selection on a Meta Level.” Machine Learning, 2022.
LibreCat | arXiv
 

2022 | Journal Article | LibreCat-ID: 33090
Gevers, Karina, et al. “A Comparison of Heuristic, Statistical, and Machine Learning Methods for Heated Tool Butt Welding of Two Different Materials.” Welding in the World, Springer Science and Business Media LLC, 2022, doi:10.1007/s40194-022-01339-9.
LibreCat | DOI
 

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.
LibreCat | DOI
 

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.
LibreCat
 

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.
LibreCat
 

2021 | Conference Paper | LibreCat-ID: 22913
Hüllermeier, Eyke, et al. Automated Machine Learning, Bounded Rationality, and Rational Metareasoning. 2021.
LibreCat
 

2021 | Preprint | LibreCat-ID: 30866
Tornede, Tanja, et al. “Towards Green Automated Machine Learning: Status Quo and Future Directions.” ArXiv:2111.05850, 2021.
LibreCat | arXiv
 

2021 | Conference Paper | LibreCat-ID: 21198
Hanselle, Jonas Manuel, et al. Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data. 2021.
LibreCat
 

2020 | Conference Paper | LibreCat-ID: 17407
Tornede, Alexander, et al. “Extreme Algorithm Selection with Dyadic Feature Representation.” Discovery Science, 2020.
LibreCat
 

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.
LibreCat
 

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.
LibreCat | DOI
 

2020 | Conference Paper | LibreCat-ID: 20306
Tornede, Alexander, et al. “Towards Meta-Algorithm Selection.” Workshop MetaLearn 2020 @ NeurIPS 2020, 2020.
LibreCat
 

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.
LibreCat
 

2019 | Conference Abstract | LibreCat-ID: 8868
Wever, Marcel Dominik, et al. Towards Automated Machine Learning for Multi-Label Classification. 2019.
LibreCat | Files available
 

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.
LibreCat | Files available
 

2019 | Conference Abstract | LibreCat-ID: 13132
Mohr, Felix, et al. “From Automated to On-The-Fly Machine Learning.” INFORMATIK 2019: 50 Jahre Gesellschaft Für Informatik – Informatik Für Gesellschaft, Gesellschaft für Informatik e.V., 2019, pp. 273–74.
LibreCat
 

2019 | Conference Paper | LibreCat-ID: 10232 | OA
Wever, Marcel Dominik, et al. Automating Multi-Label Classification Extending ML-Plan. 2019.
LibreCat | Files available
 

2017 | Conference Abstract | LibreCat-ID: 5722
Gupta, Pritha, et al. JPL: A Java-Based Software Framework for Preference Learning. 2017.
LibreCat
 

2017 | Mastersthesis | LibreCat-ID: 5724
Hetzer, Alexander, and Tanja Tornede. Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction. Universität Paderborn, 2017.
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