Profile information

Prof. Dr.  Marius Thomas Lindauer

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

  1. 2018

  2. Efficient benchmarking of algorithm configurators via model-based surrogates

    Eggensperger, K., Lindauer, M., Hoos, H. H., Hutter, F. & Leyton-Brown, K., Jan 2018, In: Machine learning. 107, 1, p. 15-41 27 p.

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

  3. Neural Networks for Predicting Algorithm Runtime Distributions

    Eggensperger, K., Lindauer, M. & Hutter, F., 2018, Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. Lang, J. (ed.). p. 1442-1448 7 p.

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

  4. Practical Automated Machine Learning for the AutoML Challenge 2018

    Feurer, M., Eggensperger, K., Falkner, S., Lindauer, M. T. & Hutter, F., 2018.

    Research output: Contribution to conference › Paper › Research

  5. Warmstarting of Model-Based Algorithm Configuration

    Lindauer, M. & Hutter, F., 2018, 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. p. 1355-1362 8 p. (Proceedings of the AAAI Conference on Artificial Intelligence).

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

  6. 2017

  7. Efficient Parameter Importance Analysis via Ablation with Surrogates

    Biedenkapp, A., Lindauer, M., Eggensperger, K., Hutter, F., Fawcett, C. & Hoos, H. H., 2 Nov 2017, Proceedings of the AAAI Conference on Artificial Intelligence.

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

  8. Improving local search in a minimum vertex cover solver for classes of networks

    Wagner, M., Friedrich, T. & Lindauer, M., 7 Jul 2017, 2017 IEEE Congress on Evolutionary Computation (CEC): Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 1704-1711 8 p.

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

  9. The Configurable SAT Solver Challenge (CSSC)

    Hutter, F., Lindauer, M., Balint, A., Bayless, S., Hoos, H. & Leyton-Brown, K., Feb 2017, In: Artificial intelligence. 243, p. 1-25 25 p.

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

  10. AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract)

    Lindauer, M., Hutter, F., Hoos, H. H. & Schaub, T., 2017, International Joint Conference on Artificial Intelligence (IJCAI 2017). Sierra, C. (ed.). p. 5025-5029 5 p.

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

  11. Open Algorithm Selection Challenge 2017 Setup and Scenarios

    Lindauer, M. T., van Rijn, J. N. & Kotthoff, L., 2017.

    Research output: Contribution to conference › Paper › Research

  12. 2016

  13. An Empirical Study of Per-instance Algorithm Scheduling

    Lindauer, M., Bergdoll, R. D. & Hutter, F., 1 Dec 2016, Learning and Intelligent Optimization. Festa, P., Sellmann, M. & Vanschoren, J. (eds.). Springer Verlag, p. 253-259 7 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10079 LNCS).

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

  14. SpyBug: Automated Bug Detection in the Configuration Space of SAT Solvers

    Manthey, N. & Lindauer, M., 11 Jun 2016, Theory and Applications of Satisfiability Testing – SAT 2016. Le Berre, D. & Creignou, N. (eds.). Springer Verlag, p. 554-561 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9710).

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

  15. Automatic construction of parallel portfolios via algorithm configuration

    Lindauer, M., Hoos, H., Leyton-Brown, K. & Schaub, T., 20 May 2016, In: Artificial intelligence. 244, p. 272-290 19 p.

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

  16. ASlib: A benchmark library for algorithm selection

    Bischl, B., Kerschke, P., Kotthoff, L., Lindauer, M., Malitsky, Y., Fréchette, A., Hoos, H., Hutter, F., Leyton-Brown, K., Tierney, K. & Vanschoren, J., Apr 2016, In: Artificial intelligence. 237, p. 41-58 18 p.

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

  17. 2015

  18. SpySMAC: Automated Configuration and Performance Analysis of SAT Solvers

    Falkner, S., Lindauer, M. & Hutter, F., 27 Oct 2015, Theory and Applications of Satisfiability Testing – SAT 2015. Heule, M. & Weaver, S. (eds.). Springer Verlag, p. 215-222 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9340).

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

  19. AutoFolio: An Automatically Configured Algorithm Selector

    Lindauer, M. T., Hoos, H., Hutter, F. & Schaub, T., 15 Aug 2015, In: Journal of Artificial Intelligence Research. 53, p. 745-778 34 p.

    Research output: Contribution to journal › Article › Research

  20. Reports on the 2015 AAAI Workshop Series

    Albrecht, S. V., Beck, J. C., Buckeridge, D. L., Botea, A., Caragea, C., Chi, C. H., Damoulas, T., Dilkina, B., Eaton, E., Fazli, P., Ganzfried, S., Giles, C. L., Guillet, S., Holte, R., Hutter, F., Koch, T., Leonetti, M., Lindauer, M., Machado, M. C., Malitsky, Y., Marcus, G., Meijer, S., Rossi, F., Shaban-Nejad, A., Thiebaux, S., Veloso, M., Walsh, T., Wang, C., Zhang, J. & Zheng, Y., 21 Jun 2015, In: AI magazine. 36, 2, p. 90-101 12 p.

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

  21. From Sequential Algorithm Selection to Parallel Portfolio Selection

    Lindauer, M., Hoos, H. H. & Hutter, F., 29 May 2015, Learning and Intelligent Optimization. Dhaenens, C., Jourdan, L. & Marmion, M.-E. (eds.). Springer Verlag, p. 1-16 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 8994).

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

  22. Auto folio: Algorithm configuration for algorithm selection

    Lindauer, M., Hoos, H. H., Schaub, T. & Hutter, F., 2015, Algorithm Configuration: papers presented at the Twenty-Ninth AAAI Conference on Artificial Intelligence. AI Access Foundation, p. 9-15 7 p. (AAAI Workshop - Technical Report).

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

  23. Published

    AutoFolio: Algorithm Configuration for Algorithm Selection.

    Lindauer, M., Hoos, H. H., Hutter, F. & Schaub, T., 2015, AAAI Workshop: Algorithm Configuration.

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

  24. Preface

    Hutter, F., Lindauer, M. & Malitsky, Y., 2015, Algorithm configuration: papers presented at the Twenty-Ninth AAAI Conference on Artificial Intelligence. p. vii (AAAI Workshop - Technical Report).

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

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