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Difan Deng

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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) NeurIPS Workshop on Time Series in the Age of Large Models. (ArXiv).

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

  3. 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

  4. 2023
  5. E-pub ahead of print

    MASIF: Meta-learned Algorithm Selection using Implicit Fidelity Information

    Ruhkopf, T., Mohan, A., Deng, D., Tornede, A., Hutter, F. & Lindauer, M., 18 Apr 2023, (E-pub ahead of print) In: Transactions on Machine Learning Research.

    Research output: Contribution to journalArticleResearchpeer review

  6. Published

    Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges

    Bischl, B., Binder, M., Lang, M., Pielok, T., Richter, J., Coors, S., Thomas, J., Ullmann, T., Becker, M., Boulesteix, A., Deng, D. & Lindauer, M., 10 Mar 2023, In: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 13, 2, 70 p., e1484.

    Research output: Contribution to journalArticleResearchpeer review

  7. 2022
  8. Published

    SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

    Lindauer, M., Eggensperger, K., Feurer, M., Biedenkapp, A., Deng, D., Benjamins, C., Sass, R. & Hutter, F., Feb 2022, In: Journal of Machine Learning Research. 2022, 23, 8 p.

    Research output: Contribution to journalArticleResearchpeer review

  9. Published

    Efficient Automated Deep Learning for Time Series Forecasting

    Deng, D., Karl, F., Hutter, F., Bischl, B. & Lindauer, M., 2022, Proceedings of the European Conference on Machine Learning (ECML).

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

  10. 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 proceedingConference contributionResearchpeer review

  11. 2021
  12. 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 proceedingConference contributionResearchpeer review

  13. 2020
  14. 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/PreprintPreprint