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Prof. Dr.  Marius Thomas Lindauer

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

  1. 2020
  2. Published

    VERFAHREN, VORRICHTUNG UND COMPUTERPROGRAMM ZUM EINSTELLEN EINES HYPERPARAMETERS

    Lindauer, M. (Inventor), Hutter, F. (Inventor), Biedenkapp, A. (Inventor) & Bozkurt, F. (Inventor), 9 Dec 2020, IPC No. G06N 7/ 00 A I, Patent No. EP3748551, Priority date 7 Jun 2019, Priority No. EP20190179116

    Research output: Patent

  3. Published

    Using AutoML to Optimize Shape Error Prediction in Milling Processes

    Denkena, B., Dittrich, M., Lindauer, M. T., Mainka, J. M. & Stürenburg, L. K., 12 Nov 2020, In: SSRN Electronic Journal. 2020, 6 p.

    Research output: Contribution to journal › Conference article › Research › peer review

  4. Published

    Best Practices for Scientific Research on Neural Architecture Search

    Lindauer, M. & Hutter, F., Nov 2020, In: Journal of Machine Learning Research. 21, 18 p.

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

  5. E-pub ahead of print

    Neural Model-based Optimization with Right-Censored Observations

    Eggensperger, K., Haase, K., Müller, P., Lindauer, M. & Hutter, F., 29 Sept 2020, (E-pub ahead of print) 11 p.

    Research output: Working paper/Preprint › Preprint

  6. Published

    Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework

    Biedenkapp, A., Bozkurt, H. F., Eimer, T., Hutter, F. & Lindauer, M. T., 24 Aug 2020, ECAI 2020 - 24th European Conference on Artificial Intelligence. De Giacomo, G., Catala, A., Dilkina, B., Milano, M., Barro, S., Bugarin, A. & Lang, J. (eds.). p. 427-434 8 p. (Frontiers in Artificial Intelligence and Applications; vol. 325).

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

  7. Published

    Learning Step-Size Adaptation in CMA-ES

    Shala, G., Biedenkapp, A., Awad, N., Adriaensen, S., Lindauer, M. & Hutter, F., 2020, Parallel Problem Solving from Nature – PPSN XVI: 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I. Bäck, T., Preuss, M., Deutz, A., Emmerich, M., Wang, H., Doerr, C. & Trautmann, H. (eds.). Cham, p. 691-706 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12269).

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

  8. Published

    Towards TempoRL Learning When to Act

    Biedenkapp, A., Rajan, R., Hutter, F. & Lindauer, M. T., 2020. 7 p.

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

  9. 2019

  10. Towards White-box Benchmarks for Algorithm Control

    Biedenkapp, A., Bozkurt, H. F., Hutter, F. & Lindauer, M., 22 Aug 2019, (E-pub ahead of print).

    Research output: Working paper/Preprint › Preprint

  11. BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters

    Lindauer, M., Eggensperger, K., Feurer, M., Biedenkapp, A., Marben, J., Müller, P. & Hutter, F., 16 Aug 2019, (E-pub ahead of print).

    Research output: Working paper/Preprint › Preprint

  12. The algorithm selection competitions 2015 and 2017

    Lindauer, M., van Rijn, J. N. & Kotthoff, L., Jul 2019, In: Artificial intelligence. 272, p. 86-100 15 p.

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

  13. Towards Automatically-Tuned Deep Neural Networks

    Mendoza, H., Klein, A., Feurer, M., Springenberg, J. T., Urban, M., Burkart, M., Dippel, M., Lindauer, M. T. & Hutter, F., 18 May 2019, Automated Machine Learning.

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

  14. Pitfalls and Best Practices in Algorithm Configuration

    Eggensperger, K., Lindauer, M. & Hutter, F., 16 Apr 2019, In: Journal of Artificial Intelligence Research. 64, p. 861-893 33 p.

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

  15. An evolution strategy with progressive episode lengths for playing games

    Fuks, L., Awad, N., Hutter, F. & Lindauer, M., 2019, Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019. Kraus, S. (ed.). p. 1234-1240 7 p. (IJCAI International Joint Conference on Artificial Intelligence).

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

  16. Automated Algorithm Selection –Predict which algorithm to use!

    Lindauer, M. T., 2019.

    Research output: Contribution to conference › Abstract › Research

  17. Hands-On Automated Machine Learning Tools: Auto-Sklearn and Auto-PyTorch

    Lindauer, M. T., 2019.

    Research output: Contribution to conference › Abstract › Research

  18. Towards Assessing the Impact of Bayesian Optimization’s Own Hyperparameters

    Lindauer, M., Feurer, M., Eggensperger, K., Biedenkapp, A. & Hutter, F., 2019, (E-pub ahead of print) DSO Workshop at IJCAI. 8 p.

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

  19. 2018

  20. CAVE: Configuration Assessment, Visualization and Evaluation

    Biedenkapp, A., Marben, J., Lindauer, M. & Hutter, F., 31 Dec 2018, Learning and Intelligent Optimization. Pardalos, P. M., Battiti, R., Brunato, M. & Kotsireas, I. (eds.). Springer Verlag, p. 115-130 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11353 LNCS).

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

  21. A case study of algorithm selection for the traveling thief problem

    Wagner, M., Lindauer, M., Mısır, M., Nallaperuma, S. & Hutter, F., Jun 2018, In: Journal of heuristics. 24, 3, p. 295-320 26 p.

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

  22. The Algorithm Selection Competition Series 2015-17

    Lindauer, M. T., van Rijn, J. N. & Kotthoff, L., 3 May 2018, (E-pub ahead of print).

    Research output: Working paper/Preprint › Preprint

  23. Selection and Configuration of Parallel Portfolios

    Lindauer, M., Hoos, H., Hutter, F. & Leyton-Brown, K., 6 Apr 2018, Handbook of Parallel Constraint Reasoning. Springer International Publishing AG, p. 583-615 33 p.

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

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