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Machine Learning Section

Organisational unit: Research Group

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Publications

  1. 2021
  2. E-pub ahead of print

    Explaining Hyperparameter Optimization via Partial Dependence Plots

    Moosbauer, J., Herbinger, J., Casalicchio, G., Lindauer, M. & Bischl, B., 8 Nov 2021, (E-pub ahead of print) Proceedings of the international conference on Neural Information Processing Systems (NeurIPS) . 21 p.

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

  3. 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

  4. Published

    Auto-PyTorch: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL

    Zimmer, L., Lindauer, M. & Hutter, F., 1 Sept 2021, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 43, 9, p. 3079-3090 12 p., 9382913.

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

  5. Published

    Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019

    Liu, Z., Pavao, A., Xu, Z., Escalera, S., Ferreira, F., Guyon, I., Hong, S., Hutter, F., Ji, R., Junior, J. C. S. J., Li, G., Lindauer, M., Luo, Z., Madadi, M., Nierhoff, T., Niu, K., Pan, C., Stoll, D., Treguer, S., Wang, J., Wang, P., Wu, C., Xiong, Y., Zela, A. & Zhang, Y., 1 Sept 2021, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 43, 9, p. 3108-3125 18 p., 9415128.

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

  6. E-pub ahead of print

    Automatic Risk Adaptation in Distributional Reinforcement Learning

    Schubert, F., Eimer, T., Rosenhahn, B. & Lindauer, M., 11 Jun 2021, (E-pub ahead of print) 14 p.

    Research output: Working paper/Preprint › Preprint

  7. Published

    Verfahren, Vorrichtung und Computerprogramm zum Erstellen eines künstlichen neuronalen Netzes

    Lindauer, M., Hutter, F., Burkart, M. & Zimmer, L., 25 Mar 2021, IPC No. G06N 3/ 08 A I, Patent No. DE102019214625, Priority date 25 Sept 2019, Priority No. DE201910214625

    Research output: Patent

  8. Published

    METHOD, DEVICE AND COMPUTER PROGRAM FOR PRODUCING A STRATEGY FOR A ROBOT

    Hutter, F., Fuks, L., Lindauer, M. & Awad, N., 14 Jan 2021, IPC No. G05B 17/ 02 A I, Patent No. US2021008718, Priority date 12 Jul 2019, Priority No. DE201910210372

    Research output: Patent

  9. Published

    Verfahren, Vorrichtung und Computerprogramm zum Erstellen einer Strategie für einen Roboter

    Hutter, F., Fuks, L., Lindauer, M. & Awad, N., 14 Jan 2021, IPC No. G05B13/02, G06N20/00, G06N3/02, Patent No. DE102019210372A1, 7 Dec 2019, Priority date 7 Dec 2019, Priority No. DE102019210372A

    Research output: Patent

  10. E-pub ahead of print

    Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization

    Guerrero-Viu, J., Hauns, S., Izquierdo, S., Miotto, G., Schrodi, S., Biedenkapp, A., Elsken, T., Deng, D., Lindauer, M. & Hutter, F., 2021, (E-pub ahead of print) ICML 2021 Workshop AutoML. 22 p.

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

  11. Published

    Bayesian Optimization with a Prior for the Optimum

    Souza, A., Nardi, L., Oliveira, L. B., Olukotun, K., Lindauer, M. & Hutter, F., 2021, Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021, Proceedings. Oliver, N., Pérez-Cruz, F., Kramer, S., Read, J. & Lozano, J. A. (eds.). Cham: Springer Nature Switzerland AG, Vol. 3. p. 265-296 32 p. (Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science); vol. 12977).

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

  12. Published

    DACBench: A Benchmark Library for Dynamic Algorithm Configuration

    Eimer, T., Biedenkapp, A., Reimer, M., Adriaensen, S., Hutter, F. & Lindauer, M. T., 2021, Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21). Zhou, Z-H. (ed.). p. 1668-1674 7 p. (IJCAI International Joint Conference on Artificial Intelligence).

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

  13. E-pub ahead of print

    HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO

    Eggensperger, K., Müller, P., Mallik, N., Feurer, M., Sass, R., Awad, N., Lindauer, M. & Hutter, F., 2021, (E-pub ahead of print) Proceedings of the international conference on Neural Information Processing Systems (NeurIPS) (Datasets and Benchmarks Track). 36 p.

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

  14. 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

  15. E-pub ahead of print

    Learning Heuristic Selection with Dynamic Algorithm Configuration

    Speck, D., Biedenkapp, A., Hutter, F., Mattmüller, R. & Lindauer, M., 2021, (E-pub ahead of print) Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS).

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

  16. E-pub ahead of print

    Prior-guided Bayesian Optimization

    Souza, A., Nardi, L., Oliveira, L. B., Olukotun, K., Lindauer, M. & Hutter, F., 2021, (E-pub ahead of print) Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021.

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

  17. E-pub ahead of print

    Self-Paced Context Evaluation for Contextual Reinforcement Learning

    Eimer, T., Biedenkapp, A., Hutter, F. & Lindauer, M., 2021, (E-pub ahead of print) Proceedings of the international conference on machine learning (ICML). 14 p.

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

  18. E-pub ahead of print

    TempoRL: Learning When to Act

    Biedenkapp, A., Rajan, R., Hutter, F. & Lindauer, M., 2021, (E-pub ahead of print) Proceedings of the international conference on machine learning (ICML). 18 p.

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

  19. E-pub ahead of print

    Well-tuned Simple Nets Excel on Tabular Datasets

    Kadra, A., Lindauer, M., Hutter, F. & Grabocka, J., 2021, (E-pub ahead of print) Proceedings of the international conference on Advances in Neural Information Processing Systems (NeurIPS 2021). 23 p.

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

  20. 2020
  21. E-pub ahead of print

    Squirrel: A Switching Hyperparameter Optimizer

    Awad, N., Shala, G., Deng, D., Mallik, N., Feurer, M., Eggensperger, K., Biedenkapp, A., Vermetten, D., Wang, H., Doerr, C., Lindauer, M. & Hutter, F., 16 Dec 2020, (E-pub ahead of print) 3 p.

    Research output: Working paper/Preprint › Preprint

  22. Published

    VERFAHREN, VORRICHTUNG UND COMPUTERPROGRAMM ZUM EINSTELLEN EINES HYPERPARAMETERS

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

    Research output: Patent

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