Profile information

Prof. Dr.  Marius Thomas Lindauer

https://orcid.org/0000-0002-9675-3175
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Publications

  1. 2026
  2. Accepted/In press

    HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization

    Wever, M. D., Muschalik, M., Fumagalli, F. & Lindauer, M., 2026, (Accepted/In press) Proceedings of the Fortieth AAAI Conference on Artificial Intelligence (AAAI 2026).

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

  3. 2025
  4. Published

    Towards Dynamic Priors in Bayesian Optimization for Hyperparameter Optimization

    Fehring, L., Wever, M., Spliethöver, M., Hennig, L., Wachsmuth, H. & Lindauer, M., 4 Nov 2025, Workshop Track of the AutoML Conference . 15 p.

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

  5. E-pub ahead of print

    Neural Attention Search

    Deng, D. & Lindauer, M., 18 Sept 2025, (E-pub ahead of print) The Thirty-Ninth Annual Conference on Neural Information Processing Systems.

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

  6. 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

  7. E-pub ahead of print

    Performance Prediction In Reinforcement Learning: The Bad And The Ugly

    Dierkes, J., Eimer, T., Lindauer, M. & Hoos, H., 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

  8. E-pub ahead of print

    Towards Exploiting Early Termination for Multi-Fidelity Hyperparameter Optimization

    Graf, H., Fehring, L., Tornede, T., Tornede, A., Wever, M. D. & Lindauer, M., Sept 2025, (E-pub ahead of print) Workshop Track of the AutoML Conference .

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

  9. Published

    Automl for Multi-Class Anomaly Compensation of Sensor Drift

    Schaller, M. C., Kruse, M., Ortega, A., Lindauer, M. & Rosenhahn, B., 15 Jun 2025, In: Measurement: Journal of the International Measurement Confederation. 250, 117097.

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

  10. 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

  11. 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

  12. Accepted/In press

    Growing with Experience: Growing Neural Networks in Deep Reinforcement Learning

    Fehring, L., Eimer, T. & Lindauer, M., 15 Feb 2025, (Accepted/In press) 2025 Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2025).

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

  13. Accepted/In press

    Moments Matter: Stabilizing Policy Optimization using Return Distributions

    Jabs, D., Mohan, A. & Lindauer, M., 15 Feb 2025, (Accepted/In press) 2025 Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2025).

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

  14. Published

    auto-sktime: Automated Time Series Forecasting

    Zöller, M., Lindauer, M. & Huber, M., 3 Jan 2025, Proceedings of the 18TH Learning and Intelligent Optimization Conference (LION). Festa, P., Ferone, D., Pastore, T. & Pisacane, O. (eds.). p. 456–471 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14990 LNCS).

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

  15. E-pub ahead of print

    Automated Data Preparation for Machine Learning

    Mladenovic, S., Lindauer, M. & Doerr, C., 2025, (E-pub ahead of print) 4th International Conference on Automated Machine Learning: Non-Archival Track.

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

  16. Accepted/In press

    Auto-nnU-Net: Towards Automated Medical Image Segmentation

    Becktepe, J., Hennig, L., Oeltze-Jafra, S. & Lindauer, M., 2025, (Accepted/In press) International Conference on Automated Machine Learning 2025.

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

  17. Accepted/In press

    DeepCAVE: A Visualization and Analysis Tool for Automated Machine Learning

    Segel, S., Graf, H., Bergman, E., Thieme, K., Wever, M. D., Tornede, A., Hutter, F. & Lindauer, M., 2025, (Accepted/In press) In: Journal of Machine Learning Research. 2025, 26

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

  18. E-pub ahead of print

    Guidelines for the Quality Assessment of Energy-Aware NAS Benchmarks

    Kocher, N., Wassermann, C., Hennig, L., Seng, J., Lindauer, M., Hoos, H., Kersting, K. & Müller, M., 2025, (E-pub ahead of print) Castanet 2025 Workshop on Challenges Advances and Sustainability in AI HPC Interaction: In conjunction with the 25th IEEE ACM International Symposium on Cluster Cloud and Internet Computing.

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

  19. Published

    How Green is AutoML for Tabular Data?

    Neutatz, F., Lindauer, M. & Abedjan, Z., 2025, Proceedings 28th International Conference on Extending Database Technology ( EDBT 2025 ). p. 350–363

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

  20. Published

    Leveraging AutoML for Sustainable Deep Learning: A MultiObjective HPO Approach on Deep Shift Neural Networks

    Hennig, L. & Lindauer, M., 2025, In: Transactions on Machine Learning Research. 2025-July

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

  21. E-pub ahead of print

    Leveraging AutoML for Sustainable Deep Learning: A Multi- Objective HPO Approach on Deep Shift Neural Networks

    Hennig, L. & Lindauer, M., 2025, (E-pub ahead of print) Transactions on Machine Learning Research.

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

  22. E-pub ahead of print

    Revisiting Learning Rate Control

    Henheik, M., Eimer, T. & Lindauer, M., 2025, (E-pub ahead of print) International Conference on Automated Machine Learning 2025.

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

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