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Institute of Artificial Intelligence

Organisational unit: Institute

Type of address: Visitor address.
Appelstraße 9a
30167
Hannover
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Publications

  1. 2024
  2. E-pub ahead of print

    Optimizing Time Series Forecasting Architectures: A Hierarchical Neural Architecture Search Approach

    Deng, D. & Lindauer, M., 10 Jun 2024, (E-pub ahead of print) (ArXiv).

    Research output: Working paper/Preprint › Preprint

  3. E-pub ahead of print

    Hyperparameter Importance Analysis for Multi-Objective AutoML

    Theodorakopoulos, D., Stahl, F. & Lindauer, M., 13 May 2024, (E-pub ahead of print).

    Research output: Working paper/Preprint › Preprint

  4. Published

    Verfahren zum Trainieren eines Algorithmus des maschinellen Lernens durch ein bestärkendes Lernverfahren

    Eimer, T., Hutter, F., Lindauer, M. & Biedenkapp, A., 4 Apr 2024, IPC No. G06N20/00, Patent No. DE102022210480A1, 4 Oct 2022, Priority date 4 Oct 2022, Priority No. DE202210210480A

    Research output: Patent

  5. E-pub ahead of print

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

    Hennig, L., Tornede, T. & Lindauer, M., 2 Apr 2024, (E-pub ahead of print) 5th Workshop on practical ML for limited/low resource settings.

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

  6. Accepted/In press

    auto-sktime: Automated Time Series Forecasting

    Zöller, M., Lindauer, M. & Huber, M., Apr 2024, (Accepted/In press) Proceedings of the 18TH Learning and Intelligent Optimization Conference (LION).

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

  7. E-pub ahead of print

    Structure in Deep Reinforcement Learning: A Survey and Open Problems

    Mohan, A., Zhang, A. & Lindauer, M., Apr 2024, (E-pub ahead of print) In: Journal of Artificial Intelligence Research.

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

  8. Published

    Who Determines What Is Relevant? Humans or AI? Why Not Both? A spectrum of human–artificial intelligence collaboration in assessing relevance

    Faggioli, G., Dietz, L., Clarke, C. L. A., Demartini, G., Hagen, M., Hauff, C., Kando, N., Kanoulas, E., Potthast, M., Stein, B. & Wachsmuth, H., 25 Mar 2024, In: Communications of the ACM. 67, 4, p. 31-34 4 p.

    Research output: Contribution to journal › Comment/debate › Research › peer review

  9. Published

    Interactive Hyperparameter Optimization in Multi-Objective Problems via Preference Learning

    Giovanelli, J., Tornede, A., Tornede, T. & Lindauer, M., 24 Mar 2024, Proceedings of the 38th conference on AAAI. Wooldridge, M., Dy, J. & Natarajan, S. (eds.). p. 12172-12180 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 38, no. 11).

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

  10. E-pub ahead of print

    AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks

    Tornede, A., Deng, D., Eimer, T., Giovanelli, J., Mohan, A., Ruhkopf, T., Segel, S., Theodorakopoulos, D., Tornede, T., Wachsmuth, H. & Lindauer, M., 9 Feb 2024, (E-pub ahead of print) In: Transactions on Machine Learning Research.

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

  11. E-pub ahead of print

    Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization

    Benjamins, C., Cenikj, G., Nikolikj, A., Mohan, A., Eftimov, T. & Lindauer, M., 2024, (E-pub ahead of print) Genetic and Evolutionary Computation Conference (GECCO).

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

  12. E-pub ahead of print

    Position Paper: A Call to Action for a Human-Centered AutoML Paradigm

    Lindauer, M., Karl, F., Klier, A., Moosbauer, J., Tornede, A., Müller, A., Hutter, F., Feurer, M. & Bischl, B., 2024, (E-pub ahead of print) Proceedings of the international conference on machine learning.

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

  13. 2023
  14. Published

    AutoML: advanced tool for mining multivariate plant traits

    Shoaib, M., Kotthoff, L., Lindauer, M. & Kant, S., Dec 2023, In: Trends in Plant Science. 28, 12, p. 1451-1452 2 p.

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

  15. Published

    Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms

    Sengupta, M., Dec 2023, Findings of the Association for Computational Linguistics: EMNLP 2023. Singapore, p. 4636–4659 24 p.

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

  16. E-pub ahead of print

    AutoML in Heavily Constrained Applications

    Neutatz, F., Lindauer, M. & Abedjan, Z., 17 Nov 2023, (E-pub ahead of print) In: VLDB Journal.

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

  17. Accepted/In press

    A Patterns Framework for Incorporating Structure in Deep Reinforcement Learning

    Mohan, A., Zhang, A. & Lindauer, M., 17 Sept 2023, (Accepted/In press) The 16th European Workshop on Reinforcement Learning (EWRL 2023).

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

  18. Accepted/In press

    Extended Abstract: AutoRL Hyperparameter Landscapes

    Mohan, A., Benjamins, C., Wienecke, K., Dockhorn, A. & Lindauer, M., 15 Sept 2023, (Accepted/In press) The 16th European Workshop on Reinforcement Learning (EWRL 2023).

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

  19. Published

    Claim Optimization in Computational Argumentation

    Skitalinskaya, G., Spliethöver, M. & Wachsmuth, H., Sept 2023, Proceedings of the 16th International Natural Language Generation Conference. Keet, C. M., Lee, H-Y. & Zarrieß, S. (eds.). p. 134-152

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

  20. Published

    Identifying Feedback Types to Augment Feedback Comment Generation

    Stahl, M. & Wachsmuth, H., Sept 2023, Proceedings of the 16th International Natural Language Generation Conference: Generation Challenges. p. 31-36

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

  21. E-pub ahead of print

    PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning

    Mallik, N., Bergman, E., Hvarfner, C., Stoll, D., Janowski, M., Lindauer, M., Nardi, L. & Hutter, F., Sept 2023, (E-pub ahead of print) Proceedings of the international Conference on Neural Information Processing Systems (NeurIPS).

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

  22. Published

    Hyperparameters in Reinforcement Learning and How to Tune Them

    Eimer, T., Lindauer, M. & Raileanu, R., 23 Jul 2023, ICML'23: Proceedings of the 40th International Conference on Machine Learning. p. 9104–9149 366

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

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