Publications
2025
- Published
Practitioner Motives to Select Hyperparameter Optimization Methods
Hasebrook, N., Morsbach, F., Kannengießer, N., Zöller, M., Franke, J., Lindauer, M., Hutter, F. & Sunyaev, A., May 2025, In: ACM Transactions on Computer-Human Interaction.Research output: Contribution to journal › Article › Research › peer review
2024
- Published
AMLTK: A Modular AutoML Toolkit in Python
Bergman, E., Feurer, M., Bahram, A., Rezaei, A., Purucker, L., Segel, S., Lindauer, M. & Eggensperger, K., 14 Aug 2024, In: The Journal of Open Source Software. 9, 100, 4 p., 6367.Research output: Contribution to journal › Article › Research › peer review
- 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
- 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
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
2023
- Published
AutoRL Hyperparameter Landscapes
Mohan, A., Benjamins, C., Wienecke, K., Dockhorn, A. & Lindauer, M., 12 Nov 2023, Conference proceeding: Second Internatinal Conference on Automated Machine Learning. 27 p. (Proceedings of Machine Learning Research; vol. 228).Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- Published
Automated Machine Learning for Remaining Useful Life Predictions
Zoeller, M., Mauthe, F., Zeiler, P., Lindauer, M. & Huber, M., 1 Oct 2023, Proceedings of the international conference on Systems Science and Engineering, Human-Machine Systems, and Cybernetics (IEEE SMC): Improving the Quality of Life, SMC 2023 - Proceedings. p. 2907-2912 6 p. (IEEE International Conference on Systems, Man, and Cybernetics).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
- E-pub ahead of print
Extended Abstract: AutoRL Hyperparameter Landscapes
Mohan, A., Benjamins, C., Wienecke, K., Dockhorn, A. & Lindauer, M., 20 Jul 2023, (E-pub ahead of print). 6 p.Research output: Contribution to conference › Abstract › 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
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
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
- E-pub ahead of print
Enhancing Explainability of Hyperparameter Optimization via Bayesian Algorithm Execution
Moosbauer, J., Casalicchio, G., Lindauer, M. & Bischl, B., 11 Jun 2022, (E-pub ahead of print).Research output: Working paper/Preprint › Preprint
- Published
PriorBand: HyperBand + Human Expert Knowledge
Mallik, N., Hvarfner, C., Stoll, D., Janowski, M., Bergman, E., Lindauer, M. T., Nardi, L. & Hutter, F., 2022, 2022 NeurIPS Workshop on Meta Learning (MetaLearn).Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- Published
π BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization.
Hvarfner, C., Stoll, D., Souza, A. L. F., Lindauer, M., Hutter, F. & Nardi, L., 2022, Proceedings of the International conference on Learning Representation (ICLR).Research output: Chapter in book/report/conference proceeding › Conference contribution › Research