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Institute of Artificial Intelligence

Organisational unit: Institute

Type of address: Visitor address.
Appelstraße 9a
30167
Hannover
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101 - 120 out of 145Page size: 20

Publications

  1. 2022
  2. Published

    HARRIS: Hybrid Ranking and Regression Forests for Algorithm Selection

    Fehring, L., Hanselle, J. & Tornede, A., 2022, NeurIPS Workshop on Meta Learning (MetaLearn 2022).

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

  3. Published

    PriorBand: HyperBand + Human Expert Knowledge

    Mallik, N., Hvarfner, C., Stoll, D., Janowski, M., Bergman, E., Lindauer, M. T., Nardi, L. & Hutter, F., 2022, 2022 NeurIPS Workshop on Meta Learning (MetaLearn).

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

  4. E-pub ahead of print

    Searching in the Forest for Local Bayesian Optimization

    Deng, D. & Lindauer, M., 2022, (E-pub ahead of print) ECML/PKDD workshop on Meta-learning. 17 p.

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

  5. 2021
  6. Published

    DEVICE AND METHOD FOR PLANNING AN OPERATION OF A TECHNICAL SYSTEM

    Spitz, J. (Inventor), Biedenkapp, A. (Inventor), Speck, D. (Inventor), Hutter, F. (Inventor), Lindauer, M. (Inventor) & Mattmueller, R. (Inventor), 9 Dec 2021, IPC No. G06N 5/ 00 A I, Patent No. US2021383245, Priority date 5 Jun 2020, Priority No. EP20200178576

    Research output: Patent

  7. Published

    Vorrichtung und Verfahren zur Planung eines Betriebs eines technischen Systems

    Spitz, J. (Inventor), Biedenkapp, A. (Inventor), Speck, D. (Inventor), Hutter, F. (Inventor), Lindauer, M. (Inventor) & Mattmueller, R. (Inventor), 9 Dec 2021, IPC No. G06Q 50/ 04 A I, Patent No. DE102020207114, Priority date 5 Jun 2020, Priority No. DE202010207114

    Research output: Patent

  8. Published

    Learning Heuristic Selection with Dynamic Algorithm Configuration

    Speck, D., Biedenkapp, A., Hutter, F., Mattmüller, R. & Lindauer, M., 5 Dec 2021, Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS). Biundo, S., Do, M., Goldman, R., Katz, M., Yang, Q. & Zhuo, H. H. (eds.). p. 597-605 9 p. (Proceedings International Conference on Automated Planning and Scheduling, ICAPS; vol. 2021-August).

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

  9. 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

  10. 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

  11. 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

  12. 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

  13. Published

    Self-Paced Context Evaluation for Contextual Reinforcement Learning

    Eimer, T., Biedenkapp, A., Hutter, F. & Lindauer, M., 18 Jul 2021, Proceedings of the international conference on machine learning (ICML). ML Research Press, p. 2948-2958 11 p. (Proceedings of Machine Learning Research; vol. 139).

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

  14. 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

  15. Published

    Verfahren, Vorrichtung und Computerprogramm zum Erstellen eines künstlichen neuronalen Netzes

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

    Research output: Patent

  16. Published

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

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

    Research output: Patent

  17. 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

  18. 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

  19. 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

  20. 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

  21. 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

  22. 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

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