Publications
- 2024
- 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
- 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
- 2023
- 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 journal › Article › Research › peer review
- 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 journal › Article › Research › peer review
- 2022
- 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 journal › Article › Research › peer review
- 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 proceeding › Conference contribution › Research › peer review
- 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
- 2021
- 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
- 2020
- 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