Publications
- 2023
- 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
- 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
- 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
- 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
- Published
Application of machine learning for fleet-based condition monitoring of ball screw drives in machine tools
Denkena, B., Dittrich, M., Noske, H., Lange, D., Benjamins, C. & Lindauer, M., Jul 2023, In: The international journal of advanced manufacturing technology. 127, 3-4, p. 1143-1164 22 p.Research output: Contribution to journal › Article › 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
- 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
- E-pub ahead of print
Symbolic Explanations for Hyperparameter Optimization
Segel, S., Graf, H., Tornede, A., Bischl, B. & Lindauer, M., 16 May 2023, (E-pub ahead of print) AutoML Conference 2023.Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- E-pub ahead of print
MASIF: Meta-learned Algorithm Selection using Implicit Fidelity Information
Ruhkopf, T., Mohan, A., Deng, D., Tornede, A., Hutter, F. & Lindauer, M., 18 Apr 2023, (E-pub ahead of print) In: Transactions on Machine Learning Research.Research output: Contribution to journal › Article › Research › peer review
- Published
Green-AutoML for Plastic Litter Detection
Theodorakopoulos, D., Manß, C., Stahl, F. & Lindauer, M., Apr 2023, Proceedings of the ICLR Workshop on Tackling Climate Change with Machine Learning. 7 p.Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- Published
POLTER: Policy Trajectory Ensemble Regularization for Unsupervised Reinforcement Learning
Schubert, F., Benjamins, C., Döhler, S., Rosenhahn, B. & Lindauer, M., Apr 2023, In: Transactions on Machine Learning Research. 2023, 4Research output: Contribution to journal › Article › Research › peer review
- Published
Synergizing Theory and Practice of Automated Algorithm Design for Optimization (Dagstuhl Seminar 23332).
Vermetten, D., Krejca, M. S., Lindauer, M., López-Ibáñez, M. & Malan, K. M., 13 Mar 2023, In: Dagstuhl Reports. 13, 8, 25 p.Research output: Contribution to journal › Conference article › Research › peer review
- Published
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges
Bischl, B., Binder, M., Lang, M., Pielok, T., Richter, J., Coors, S., Thomas, J., Ullmann, T., Becker, M., Boulesteix, A., Deng, D. & Lindauer, M., 10 Mar 2023, In: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 13, 2, 70 p., e1484.Research output: Contribution to journal › Article › Research › peer review
- E-pub ahead of print
Automated Machine Learning for Remaining Useful Life Predictions
Zoeller, M., Mauthe, F., Zeiler, P., Lindauer, M. & Huber, M., 2023, (E-pub ahead of print) Proceedings of the international conference on Systems Science and Engineering, Human-Machine Systems, and Cybernetics (IEEE SMC).Research output: Chapter in book/report/conference proceeding › Conference contribution › 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
- Accepted/In press
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
Benjamins, C., Raponi, E., Jankovic, A., Doerr, C. & Lindauer, M., 2023, (Accepted/In press) AutoML Conference 2023.Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- Accepted/In press
Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
Benjamins, C., Raponi, E., Jankovic, A., Doerr, C. & Lindauer, M., 2023, (Accepted/In press) GECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference Companion.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
Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis
Benjamins, C., Jankovic, A., Raponi, E., Blom, K. V. D., Lindauer, M. & Doerr, C., 17 Nov 2022.Research output: Contribution to conference › Paper › Research › peer review