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Carolin Benjamins

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Publications

  1. 2025
  2. E-pub ahead of print

    Mighty: A Comprehensive Tool for studying Generalization, Meta-RL and AutoRL

    Mohan, A., Eimer, T., Benjamins, C., Lindauer, M. & Biedenkapp, A., Sept 2025, (E-pub ahead of print) 18th European Workshop on Reinforcement Learning (EWRL).

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

  3. E-pub ahead of print

    SynthACticBench: A Capability-Based Synthetic Benchmark for Algorithm Configuration

    Margraf, V., Lappe, A., Wever, M. D., Benjamins, C., Hüllermeier, E. & Lindauer, M., Jun 2025, (E-pub ahead of print) GECCO 2025 - Proceedings of the 2025 Genetic and Evolutionary Computation Conference . Association for Computing Machinery (ACM), (ACM Conferences).

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

  4. Published

    MO-SMAC: Multi-objective Sequential Model-based Algorithm Configuration

    Rook, J., Benjamins, C., Bossek, J., Trautmann, H., Hoos, H. & Lindauer, M., 10 Mar 2025, In: Evolutionary computation. 25, 1, p. 1-25

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

  5. 2024
  6. E-pub ahead of print

    Bayesian Optimization for Protein Sequence Design: Back to Simplicity with Gaussian Processes

    Benjamins, C., Surana, S., Bent, O., Lindauer, M. & Duckworth, P., Dec 2024, (E-pub ahead of print) AI for Accelerated Materials Design - NeurIPS Workshop 2024.

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

  7. Published

    Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization

    Benjamins, C., Cenikj, G., Nikolikj, A., Mohan, A., Eftimov, T. & Lindauer, M., 1 Aug 2024, Genetic and Evolutionary Computation Conference (GECCO). p. 563 - 566

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

  8. 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

  9. Published

    Bayesian Optimisation for Protein Sequence Design: Gaussian Processes with Zero-Shot Protein Language Model Prior Mean

    Benjamins, C., Surana, S., Bent, O., Lindauer, M. & Duckworth, P., 2024. 12 p.

    Research output: Contribution to conference › Paper › Research › peer review

  10. 2023
  11. 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

  12. Published

    Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization

    Benjamins, C., Raponi, E., Jankovic, A., Doerr, C. & Lindauer, M., 24 Jul 2023, GECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference Companion. p. 483 - 486 4 p.

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

  13. 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

  14. 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

  15. 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.

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

  16. 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

  17. 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

  18. 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

  19. 2022
  20. 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

  21. E-pub ahead of print

    PI is back! Switching Acquisition Functions in Bayesian Optimization

    Benjamins, C., Raponi, E., Jankovic, A., Blom, K. V. D., Santoni, M. L., Lindauer, M. & Doerr, C., 2 Nov 2022, (E-pub ahead of print).

    Research output: Working paper/Preprint › Preprint

  22. Published

    SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

    Lindauer, M., Eggensperger, K., Feurer, M., Biedenkapp, A., Deng, D., Benjamins, C., Sass, R. & Hutter, F., Feb 2022, In: Journal of Machine Learning Research. 2022, 23, 8 p.

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

  23. 2021
  24. 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

  25. 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