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Publications

  1. 2024
  2. 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 proceedingConference contributionResearchpeer review

  3. 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 proceedingConference contributionResearchpeer review

  4. 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 journalArticleResearchpeer review

  5. 2023
  6. Published

    PyExperimenter: Easily distribute experiments and track results

    Tornede, T., Tornede, A., Fehring, L., Gehring, L., Graf, H., Hanselle, J., Mohr, F. & Wever, M., 20 Apr 2023, In: Journal of Open Source Software. 3 p.

    Research output: Contribution to journalArticleResearchpeer review

  7. Algorithm selection on a meta level

    Tornede, A., Gehring, L., Tornede, T., Wever, M. & Hüllermeier, E., Apr 2023, In: Machine learning. 112, 4, p. 1253-1286 34 p.

    Research output: Contribution to journalArticleResearchpeer review

  8. Towards Green Automated Machine Learning: Status Quo and Future Directions

    Tornede, T., Tornede, A., Hanselle, J., Mohr, F., Wever, M. & Hüllermeier, E., 2023, In: Journal of Artificial Intelligence Research. 77, p. 427-457 31 p.

    Research output: Contribution to journalArticleResearchpeer review

  9. 2021
  10. Coevolution of remaining useful lifetime estimation pipelines for automated predictive maintenance

    Tornede, T., Tornede, A., Wever, M. & Hüllermeier, E., 26 Jun 2021, GECCO 2021 - Proceedings of the 2021 Genetic and Evolutionary Computation Conference. p. 368-376 9 p. (ACM Conferences).

    Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

  11. AutoML for Predictive Maintenance: One Tool to RUL Them All

    Tornede, T., Tornede, A., Wever, M., Mohr, F. & Hüllermeier, E., 10 Jan 2021, IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning: Second International Workshop, IoT Streams 2020, and First International Workshop, ITEM 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, Revised Selected Papers. Gama, J., Pashami, S., Bifet, A., Sayed-Mouchawe, M., Fröning, H., Pernkopf, F., Schiele, G. & Blott, M. (eds.). 1 ed. Springer Science and Business Media Deutschland GmbH, p. 106–118 13 p. (Communications in Computer and Information Science; vol. 1325).

    Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

  12. 2020
  13. Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions

    Hoffmann, M. W., Wildermuth, S., Gitzel, R., Boyaci, A., Gebhardt, J., Kaul, H., Amihai, I., Forg, B., Suriyah, M., Leibfried, T., Stich, V., Hicking, J., Bremer, M., Kaminski, L., Beverungen, D., Heiden, P. Z. & Tornede, T., 8 Apr 2020, In: Sensors. 20, 7, 2099.

    Research output: Contribution to journalArticleResearchpeer review