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Dr.  Marcel Dominik Wever

https://orcid.org/0000-0001-9782-6818
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Publications

  1. 2021

  2. AutoML for Multi-Label Classification: Overview and Empirical Evaluation

    Wever, M., Tornede, A., Mohr, F. & Hullermeier, E., 1 Sept 2021, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 43, 9, p. 3037-3054 18 p., 9321731.

    Research output: Contribution to journal › Review article › Research › peer review

  3. Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning

    Mohr, F., Wever, M., Tornede, A. & Hullermeier, E., 1 Sept 2021, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 43, 9, p. 3055-3066 12 p., 9347828.

    Research output: Contribution to journal › Article › Research › peer review

  4. Coevolution of remaining useful lifetime estimation pipelines for automated predictive maintenance

    Tornede, T., Tornede, A., Wever, M. & Hüllermeier, E., 26 Jun 2021, GECCO 2021 - Proceedings of the 2021 Genetic and Evolutionary Computation Conference. p. 368-376 9 p. (ACM Conferences).

    Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

  5. AutoML for Predictive Maintenance: One Tool to RUL Them All

    Tornede, T., Tornede, A., Wever, M., Mohr, F. & Hüllermeier, E., 10 Jan 2021, IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning: Second International Workshop, IoT Streams 2020, and First International Workshop, ITEM 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, Revised Selected Papers. Gama, J., Pashami, S., Bifet, A., Sayed-Mouchawe, M., Fröning, H., Pernkopf, F., Schiele, G. & Blott, M. (eds.). 1 ed. Springer Science and Business Media Deutschland GmbH, p. 106–118 13 p. (Communications in Computer and Information Science; vol. 1325).

    Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

  6. Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data

    Hanselle, J., Tornede, A., Wever, M. & Hüllermeier, E., 2021, Advances in Knowledge Discovery and Data Mining - 25th Pacific-Asia Conference, PAKDD 2021, Proceedings. Karlapalem, K., Cheng, H., Ramakrishnan, N., Agrawal, R. K., Reddy, P. K., Srivastava, J. & Chakraborty, T. (eds.). Springer Science and Business Media Deutschland GmbH, p. 152-163 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12712 LNAI).

    Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

  7. Automated Machine Learning, Bounded Rationality, and Rational Metareasoning

    Hüllermeier, E., Mohr, F., Tornede, A. & Wever, M. D., 2021, ECML/PKDD workshop on Automating Data Science (ADS 2021).

    Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

  8. Replacing the Ex-Def Baseline in AutoML by Naive AutoML

    Mohr, F. & Wever, M., 2021, Proceedings of the 8th ICML Workshop on Automated Machine Learning. 16 p.

    Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

  9. 2020

  10. Towards Meta-Algorithm Selection

    Tornede, A., Wever, M. & Hüllermeier, E., 17 Nov 2020, (E-pub ahead of print) (4th Workshop on Meta-Learning at NeurIPS 2020).

    Research output: Working paper/Preprint › Preprint

  11. Extreme Algorithm Selection with Dyadic Feature Representation

    Tornede, A., Wever, M. & Hüllermeier, E., 2020, Discovery Science - 23rd International Conference, DS 2020, Proceedings. Appice, A., Tsoumakas, G., Manolopoulos, Y. & Matwin, S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 309-324 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12323 LNAI).

    Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

  12. Hybrid ranking and regression for algorithm selection

    Hanselle, J., Tornede, A., Wever, M. & Hüllermeier, E., 2020, KI 2020: Advances in Artificial Intelligence - 43rd German Conference on AI, Proceedings. Schmid, U., Wolter, D. & Klügl, F. (eds.). Springer Science and Business Media Deutschland GmbH, p. 59-72 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12325 LNAI).

    Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

  13. LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-label Classification

    Wever, M., Tornede, A., Mohr, F. & Hüllermeier, E., 2020, Advances in Intelligent Data Analysis XVIII - 18th International Symposium on Intelligent Data Analysis, IDA 2020, Proceedings. Berthold, M. R., Feelders, A. & Krempl, G. (eds.). Springer, p. 561-573 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12080 LNCS).

    Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

  14. Published

    Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction.

    Heid, S., Wever, M. & Hüllermeier, E., 2020, In: Computing Research Repository (CoRR). abs/2008.01377

    Research output: Contribution to journal › Article › Research › peer review

  15. Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis

    Tornede, A., Wever, M., Werner, S., Mohr, F. & Hüllermeier, E., 2020, Proceedings of The 12th Asian Conference on Machine Learning. Vol. 129. p. 737-752 16 p. (Proceedings of Machine Learning Research).

    Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

  16. 2019

  17. Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking

    Tornede, A., Wever, M. D. & Hüllermeier, E., 2019, 29th Workshop Computational Intelligence.

    Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

  18. Automating Multi-Label Classification Extending ML-Plan

    Wever, M. D., Mohr, F., Tornede, A. & Hüllermeier, E., 2019, ICML 2019 Workshop AutoML.

    Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

  19. From Automated to On-The-Fly Machine Learning

    Mohr, F., Wever, M. D., Tornede, A. & Hüllermeier, E., 2019, INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik–Informatik für Gesellschaft.

    Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

  20. Multioracle coevolutionary learning of requirements specifications from examples in on-the-fly markets

    Wever, M., Van Rooijen, L. & Hamann, H., 2019, In: Evolutionary computation. 28, 2, p. 165-193 29 p.

    Research output: Contribution to journal › Article › Research › peer review

  21. 2018

  22. Automated Multi-Label Classification based on ML-Plan

    Wever, M., Mohr, F. & Hüllermeier, E., Nov 2018, In: Computing Research Repository (CoRR). November 2018

    Research output: Contribution to journal › Article › Research › peer review

  23. ML-Plan: Automated machine learning via hierarchical planning

    Mohr, F., Wever, M. & Hüllermeier, E., 1 Sept 2018, In: Machine learning. 107, 8-10, p. 1495-1515 21 p.

    Research output: Contribution to journal › Article › Research › peer review

  24. Automated Machine Learning Service Composition

    Mohr, F., Wever, M. & Hüllermeier, E., Sept 2018, In: Computing Research Repository (CoRR). September 2018

    Research output: Contribution to journal › Article › Research › peer review

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