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Dr.  Theresa Eimer

https://orcid.org/0000-0001-5561-5908
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Publications

  1. 2025
  2. E-pub ahead of print

    Mighty: A Comprehensive Tool for studying Generalization, Meta-RL and AutoRL

    Mohan, A., Eimer, T., Benjamins, C., Lindauer, M. & Biedenkapp, A., Sept 2025, (E-pub ahead of print) 18th European Workshop on Reinforcement Learning (EWRL).

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

  3. E-pub ahead of print

    Performance Prediction In Reinforcement Learning: The Bad And The Ugly

    Dierkes, J., Eimer, T., Lindauer, M. & Hoos, H., Sept 2025, (E-pub ahead of print) 18th European Workshop on Reinforcement Learning (EWRL).

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

  4. Accepted/In press

    Growing with Experience: Growing Neural Networks in Deep Reinforcement Learning

    Fehring, L., Eimer, T. & Lindauer, M., 15 Feb 2025, (Accepted/In press) 2025 Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2025).

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

  5. E-pub ahead of print

    Best Practices For Empirical Meta-Algorithmic Research: Guidelines from the COSEAL Research Network

    Eimer, T., Schäpermeier, L., Biedenkapp, A., Tornede, A., Kotthoff, L., Leyman, P., Feurer, M., Eggensperger, K., Maile, K., Tornede, T., Kozak, A., Xue, K., Wever, M. D., Baratchi, M., Pulatov, D., Trautmann, H., Kashgarani, H. & Lindauer, M., 2025, (E-pub ahead of print).

    Research output: Working paper/Preprint › Preprint

  6. E-pub ahead of print

    Revisiting Learning Rate Control

    Henheik, M., Eimer, T. & Lindauer, M., 2025, (E-pub ahead of print) International Conference on Automated Machine Learning 2025.

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

  7. E-pub ahead of print

    Task Scheduling & Forgetting in Multi-Task Reinforcement Learning

    Speckmann, M. & Eimer, T., 2025, (E-pub ahead of print) Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2025).

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

  8. 2024
  9. Published

    Reinforcing automated machine learning: bridging AutoML and reinforcement learning

    Eimer, T., 21 Nov 2024, Hannover. 91 p.

    Research output: Thesis › Doctoral thesis

  10. Published

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

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

    Research output: Patent

  11. 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

  12. E-pub ahead of print

    ARLBench: Flexible and Efficient Benchmarking for Hyperparameter Optimization in Reinforcement Learning

    Becktepe, J., Dierkes, J., Benjamins, C., Mohan, A., Salinas, D., Rajan, R., Hutter, F., Hoos, H., Lindauer, M. & Eimer, T., 2024, (E-pub ahead of print) 17th European Workshop on Reinforcement Learning (EWRL 2024).

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

  13. 2023
  14. 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

  15. 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.

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

  16. E-pub ahead of print

    Extended Abstract: 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., 2023, (E-pub ahead of print) 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

    Extended Abstract: Hyperparameters in Reinforcement Learning and How To Tune Them

    Eimer, T., Lindauer, M. & Raileanu, R., 2023, (E-pub ahead of print) The 16th European Workshop on Reinforcement Learning (EWRL 2023).

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

  18. 2022
  19. Published

    Automated Dynamic Algorithm Configuration

    Adriaensen, S., Biedenkapp, A., Shala, G., Awad, N., Eimer, T., Lindauer, M. & Hutter, F., 30 Dec 2022, In: Journal of Artificial Intelligence Research. 75, p. 1633-1699 67 p.

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

  20. Published

    Automated Reinforcement Learning (AutoRL): A Survey and Open Problems

    Parker-Holder, J., Rajan, R., Song, X., Biedenkapp, A., Miao, Y., Eimer, T., Zhang, B., Nguyen, V., Calandra, R., Faust, A., Hutter, F. & Lindauer, M., 1 Jun 2022, In: Journal of Artificial Intelligence Research. 74, 74, p. 517-568 52 p.

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

  21. 2021
  22. E-pub ahead of print

    CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning

    Benjamins, C., Eimer, T., Schubert, F., Biedenkapp, A., Rosenhahn, B., Hutter, F. & Lindauer, M., 5 Oct 2021, (E-pub ahead of print) Workshop on Ecological Theory of Reinforcement Learning, NeurIPS 2021. 20 p.

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

  23. Published

    Self-Paced Context Evaluation for Contextual Reinforcement Learning

    Eimer, T., Biedenkapp, A., Hutter, F. & Lindauer, M., 18 Jul 2021, Proceedings of the international conference on machine learning (ICML). ML Research Press, p. 2948-2958 11 p. (Proceedings of Machine Learning Research; vol. 139).

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

  24. E-pub ahead of print

    Automatic Risk Adaptation in Distributional Reinforcement Learning

    Schubert, F., Eimer, T., Rosenhahn, B. & Lindauer, M., 11 Jun 2021, (E-pub ahead of print) 14 p.

    Research output: Working paper/Preprint › Preprint

  25. Published

    DACBench: A Benchmark Library for Dynamic Algorithm Configuration

    Eimer, T., Biedenkapp, A., Reimer, M., Adriaensen, S., Hutter, F. & Lindauer, M. T., 2021, Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21). Zhou, Z.-H. (ed.). p. 1668-1674 7 p. (IJCAI International Joint Conference on Artificial Intelligence).

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

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