Publications
- 2024
- 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. DE202210210480AResearch output: Patent
- 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
- 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
- 2023
- 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 366Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- 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, 6Research output: Contribution to journal › Article › Research › peer review
- 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
- 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
- 2022
- 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
- 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
- 2021
- 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
- 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, 14 p. (Proceedings of Machine Learning Research).Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- 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
- 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
- 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
- 2020
- 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 › Conference contribution › Research › peer review