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Dr.  Theresa Eimer

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

  1. 2025
  2. 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

  3. Published

    Task Scheduling & Forgetting in Multi-Task Reinforcement Learning

    Speckmann, M. & Eimer, T., 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

  4. 2024
  5. 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

  6. 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

  7. 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

  8. 2023
  9. 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

  10. 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

  11. 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

  12. 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

  13. 2022
  14. Published

    Automated Dynamic Algorithm Configuration

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

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

  15. 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

  16. 2021
  17. 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

  18. 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

  19. 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

  20. 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

  21. Published

    Hyperparameters in Contextual RL are Highly Situational

    Eimer, T., Benjamins, C. & Lindauer, M. T., 2021, International Workshop on Ecological Theory of RL (at NeurIPS).

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

  22. 2020
  23. Published

    Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework

    Biedenkapp, A., Bozkurt, H. F., Eimer, T., Hutter, F. & Lindauer, M. T., 24 Aug 2020, ECAI 2020 - 24th European Conference on Artificial Intelligence. De Giacomo, G., Catala, A., Dilkina, B., Milano, M., Barro, S., Bugarin, A. & Lang, J. (eds.). p. 427-434 8 p. (Frontiers in Artificial Intelligence and Applications; vol. 325).

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