Publications
- 2024
- E-pub ahead of print
Bayesian Optimisation for Protein Sequence Design: Gaussian Processes with Zero-Shot Protein Language Model Prior Mean
Benjamins, C., Surana, S., Bent, O., Lindauer, M. & Duckworth, P., Dec 2024, (E-pub ahead of print) NeurIPS Workshop on Time Series in the Age of Large Models.Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- E-pub ahead of print
Bayesian Optimization for Protein Sequence Design: Back to Simplicity with Gaussian Processes
Benjamins, C., Surana, S., Bent, O., Lindauer, M. & Duckworth, P., Dec 2024, (E-pub ahead of print) AI for Accelerated Materials Design - NeurIPS Workshop 2024.Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- E-pub ahead of print
Automl for Multi-Class Anomaly Compensation of Sensor Drift
Schaller, M. C., Kruse, M., Ortega, A., Lindauer, M. & Rosenhahn, B., Nov 2024, (E-pub ahead of print).Research output: Working paper/Preprint › Preprint
- Accepted/In press
How Green is AutoML for Tabular Data?
Neutatz, F., Lindauer, M. & Abedjan, Z., Jan 2025, Proceedings of EDBT 2025.Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- Accepted/In press
Towards Enhancing Predictive Representations using Relational Structure in Reinforcement Learning
Mohan, A. & Lindauer, M., 30 Sept 2024, (Accepted/In press) The 17th European Workshop on Reinforcement Learning (EWRL 2024).Research output: Chapter in book/report/conference proceeding › Conference abstract › Research › peer review
- Published
Ultralight vector dark matter search using data from the KAGRA O3GK run
LIGO Scientific, Virgo, and KAGRA Collaborations, L. S. V. A. K. C., Brinkmann, M., Carlassara, M., Chakraborty, P., Danzmann, K., Heurs, M., Johny, N., Junker, J., Knust, N., Lehmann, J., Lück, H., Matiushechkina, M., Nery, M., Schulte, B. W., Vahlbruch, H., Wilken, D., Willke, B., Wu, D. S., Affeldt, C., Bergamin, F., Bisht, A., Bode, N., Booker, P., Borchers, A., Brockmüller, E., Carter, J., Ghosh, S., Hochheim, S., Kastaun, W., Khan, F., Koch, P., Kringel, V., Kuehn, G., Lough, J., Maciy, R. R., Meylahn, F., Nadji, S., Ohme, F., Pascale, G., Schneewind, M., Schutz, B. F., Venneberg, J., von Wrangel, J., Weinert, M., Wellmann, F. & Weßels, P., 15 Aug 2024, In: Physical Review D. 110, 4, p. 1-21 21 p., 042001.Research output: Contribution to journal › Article › Research › peer review
- Published
AMLTK: A Modular AutoML Toolkit in Python
Bergman, E., Feurer, M., Bahram, A., Rezaei, A., Purucker, L., Segel, S., Lindauer, M. & Eggensperger, K., 14 Aug 2024, In: The Journal of Open Source Software. 9, 100, 4 p., 6367.Research output: Contribution to journal › Article › Research › peer review
- Published
Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness
Spliethöver, M., Menon, S. N. & Wachsmuth, H., Aug 2024, Findings of the Association for Computational Linguistics ACL 2024. Ku, L.-W., Martins, A. & Srikumar, V. (eds.). p. 9294-9313 20 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- Accepted/In press
Hyperparameter Importance Analysis for Multi-Objective AutoML
Theodorakopoulos, D., Stahl, F. & Lindauer, M., 4 Jul 2024, (Accepted/In press) Proceedings of the european conference on AI (ECAI).Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- Published
AutoML in Heavily Constrained Applications
Neutatz, F., Lindauer, M. & Abedjan, Z., Jul 2024, In: VLDB Journal. 33, 4, p. 957–979 23 p.Research output: Contribution to journal › Article › Research › peer review
- E-pub ahead of print
Position: Why We Must Rethink Empirical Research in Machine Learning
Herrmann, M., Lange, F. J. D., Eggensperger, K., Casalicchio, G., Wever, M., Feurer, M., Rügamer, D., Hüllermeier, E., Boulesteix, A. & Bischl, B., Jul 2024, (E-pub ahead of print) Proceedings of the international conference on machine learning.Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
- E-pub ahead of print
ALPBench: A Benchmark for Active Learning Pipelines on Tabular Data
Margraf, V., Wever, M., Gilhuber, S., Tavares, G. M., Seidl, T. & Hüllermeier, E., 15 Jun 2024, (E-pub ahead of print).Research output: Working paper/Preprint › Preprint
- 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 proceeding › Conference contribution › Research › peer review
- Published
Analyzing the Use of Metaphors in News Editorials for Political Framing
Sengupta, M., El Baff, R., Alshomary, M. & Wachsmuth, H., Jun 2024, Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Duh, K., Gomez, H. & Bethard, S. (eds.). Mexico City, Mexico, p. 3621–3631 11 p. (Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024; vol. 1).Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- Published
A School Student Essay Corpus for Analyzing Interactions of Argumentative Structure and Quality
Stahl, M., Michel, N., Kilsbach, S., Schmidtke, J., Rezat, S. & Wachsmuth, H., Jun 2024, Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). Duh, K., Gomez, H. & Bethard, S. (eds.). p. 2661–2674 14 p. (Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024; vol. 1).Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- Published
Exploring LLM Prompting Strategies for Joint Essay Scoring and Feedback Generation
Stahl, M., Biermann, L., Nehring, A. & Wachsmuth, H., Jun 2024, Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024). p. 283–298Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
- Published
Verfahren zum Trainieren eines Algorithmus des maschinellen Lernens durch ein bestärkendes Lernverfahren
Eimer, T. (Inventor), Hutter, F. (Inventor), Lindauer, M. (Inventor) & Biedenkapp, A. (Inventor), 4 Apr 2024, IPC No. G06N20/00, Patent No. DE102022210480A1, 4 Oct 2022, Priority date 4 Oct 2022, Priority No. DE202210210480AResearch output: Patent
- 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
- 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
- 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