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Machine Learning Section

Organisational unit: Research Group

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Publications

  1. 2023
  2. 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

  3. 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

  4. 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

  5. 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

  6. E-pub ahead of print

    AutoRL Hyperparameter Landscapes

    Mohan, A., Benjamins, C., Wienecke, K., Dockhorn, A. & Lindauer, M., 20 Jul 2023, (E-pub ahead of print) Second International Conference on Automated Machine Learning.

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

  7. Published

    Configuration and Evaluation

    Hanselle, J., Hüllermeier, E., Mohr, F., Ngomo, A. C. N., Sherif, M. A., Tornede, A. & Wever, M. D., 22 Jun 2023, On-The-Fly Computing -- Individualized IT-services in dynamic markets.

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

  8. 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

  9. 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

  10. 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

  11. Published

    PyExperimenter: Easily distribute experiments and track results

    Tornede, T., Tornede, A., Fehring, L., Gehring, L., Graf, H., Hanselle, J., Mohr, F. & Wever, M., 20 Apr 2023, In: Journal of Open Source Software. 3 p.

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

  12. 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

  13. 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

  14. 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, 4

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

  15. 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

  16. Published

    A Survey of Methods for Automated Algorithm Configuration (Extended Abstract)

    Schede, E., Brandt, J., Tornede, A., Wever, M., Bengs, V., Hüllermeier, E. & Tierney, K., 2023, Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023. Elkind, E. (ed.). p. 6964-6968 5 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2023-August).

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

  17. 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

  18. 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

  19. 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

  20. E-pub ahead of print

    Iterative Deepening Hyperband

    Brandt, J., Wever, M., Iliadis, D., Bengs, V. & Hüllermeier, E., 2023, (E-pub ahead of print) (CoRR).

    Research output: Working paper/Preprint › Preprint

  21. 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

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