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Machine Learning Section

Organisational unit: Research Group

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Publications

  1. 2024
  2. Accepted/In press

    Hyperparameter Importance Analysis for Multi-Objective AutoML

    Theodorakopoulos, D., Stahl, F. & Lindauer, M., 4 Jul 2024, (Accepted/In press) Proceedings of the european conference on AI (ECAI).

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

  3. E-pub ahead of print

    Optimizing Time Series Forecasting Architectures: A Hierarchical Neural Architecture Search Approach

    Deng, D. & Lindauer, M., 10 Jun 2024, (E-pub ahead of print) (ArXiv).

    Research output: Working paper/Preprint › Preprint

  4. Published

    Verfahren zum Trainieren eines Algorithmus des maschinellen Lernens durch ein bestärkendes Lernverfahren

    Eimer, T., Hutter, F., Lindauer, M. & Biedenkapp, A., 4 Apr 2024, IPC No. G06N20/00, Patent No. DE102022210480A1, 4 Oct 2022, Priority date 4 Oct 2022, Priority No. DE202210210480A

    Research output: Patent

  5. E-pub ahead of print

    Towards Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks

    Hennig, L., Tornede, T. & Lindauer, M., 2 Apr 2024, (E-pub ahead of print) 5th Workshop on practical ML for limited/low resource settings.

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

  6. Accepted/In press

    auto-sktime: Automated Time Series Forecasting

    Zöller, M., Lindauer, M. & Huber, M., Apr 2024, (Accepted/In press) Proceedings of the 18TH Learning and Intelligent Optimization Conference (LION).

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

  7. E-pub ahead of print

    Structure in Deep Reinforcement Learning: A Survey and Open Problems

    Mohan, A., Zhang, A. & Lindauer, M., Apr 2024, (E-pub ahead of print) In: Journal of Artificial Intelligence Research.

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

  8. Published

    Interactive Hyperparameter Optimization in Multi-Objective Problems via Preference Learning

    Giovanelli, J., Tornede, A., Tornede, T. & Lindauer, M., 24 Mar 2024, Proceedings of the 38th conference on AAAI. Wooldridge, M., Dy, J. & Natarajan, S. (eds.). p. 12172-12180 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 38, no. 11).

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

  9. E-pub ahead of print

    AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks

    Tornede, A., Deng, D., Eimer, T., Giovanelli, J., Mohan, A., Ruhkopf, T., Segel, S., Theodorakopoulos, D., Tornede, T., Wachsmuth, H. & Lindauer, M., 9 Feb 2024, (E-pub ahead of print) In: Transactions on Machine Learning Research.

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

  10. E-pub ahead of print

    Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization

    Benjamins, C., Cenikj, G., Nikolikj, A., Mohan, A., Eftimov, T. & Lindauer, M., 2024, (E-pub ahead of print) Genetic and Evolutionary Computation Conference (GECCO).

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

  11. E-pub ahead of print

    Position Paper: A Call to Action for a Human-Centered AutoML Paradigm

    Lindauer, M., Karl, F., Klier, A., Moosbauer, J., Tornede, A., Müller, A., Hutter, F., Feurer, M. & Bischl, B., 2024, (E-pub ahead of print) Proceedings of the international conference on machine learning.

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

  12. 2023
  13. Published

    AutoML: advanced tool for mining multivariate plant traits

    Shoaib, M., Kotthoff, L., Lindauer, M. & Kant, S., Dec 2023, In: Trends in Plant Science. 28, 12, p. 1451-1452 2 p.

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

  14. E-pub ahead of print

    AutoML in Heavily Constrained Applications

    Neutatz, F., Lindauer, M. & Abedjan, Z., 17 Nov 2023, (E-pub ahead of print) In: VLDB Journal.

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

  15. Accepted/In press

    A Patterns Framework for Incorporating Structure in Deep Reinforcement Learning

    Mohan, A., Zhang, A. & Lindauer, M., 17 Sept 2023, (Accepted/In press) The 16th European Workshop on Reinforcement Learning (EWRL 2023).

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

  16. Accepted/In press

    Extended Abstract: AutoRL Hyperparameter Landscapes

    Mohan, A., Benjamins, C., Wienecke, K., Dockhorn, A. & Lindauer, M., 15 Sept 2023, (Accepted/In press) The 16th European Workshop on Reinforcement Learning (EWRL 2023).

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

  17. E-pub ahead of print

    PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning

    Mallik, N., Bergman, E., Hvarfner, C., Stoll, D., Janowski, M., Lindauer, M., Nardi, L. & Hutter, F., Sept 2023, (E-pub ahead of print) Proceedings of the international Conference on Neural Information Processing Systems (NeurIPS).

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

  18. Published

    Hyperparameters in Reinforcement Learning and How to Tune Them

    Eimer, T., Lindauer, M. & Raileanu, R., 23 Jul 2023, ICML'23: Proceedings of the 40th International Conference on Machine Learning. p. 9104–9149 366

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

  19. E-pub ahead of print

    AutoRL Hyperparameter Landscapes

    Mohan, A., Benjamins, C., Wienecke, K., Dockhorn, A. & Lindauer, M., 20 Jul 2023, (E-pub ahead of print) Second International Conference on Automated Machine Learning.

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

  20. Published

    Configuration and Evaluation

    Hanselle, J., Hüllermeier, E., Mohr, F., Ngomo, A. C. N., Sherif, M. A., Tornede, A. & Wever, M., 22 Jun 2023, On-The-Fly Computing -- Individualized IT-services in dynamic markets.

    Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research

  21. E-pub ahead of print

    Contextualize Me – The Case for Context in Reinforcement Learning

    Benjamins, C., Eimer, T., Schubert, F. G., Mohan, A., Döhler, S., Biedenkapp, A., Rosenhahn, B., Hutter, F. & Lindauer, M., 5 Jun 2023, (E-pub ahead of print) In: Transactions on Machine Learning Research. 2023, 6

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

  22. Accepted/In press

    Learning Activation Functions for Sparse Neural Networks

    Loni, M., Mohan, A., Asadi, M. & Lindauer, M., 16 May 2023, (Accepted/In press) Second International Conference on Automated Machine Learning.

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

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