Institute of Informatics
Chair of Artificial Intelligence and Machine Learning
Prof. Dr. Eyke Hüllermeier
My research is centered around automated machine learning (AutoML) and related topics such as algorithm selection, ensemble construction, self-supervised learning and active learning. I am particularly interested in the combination of self-supervised learning with active learning methodologies in partially labeled settings, to sample the most informative data instances to improve performance on a given task.
Automated Machine Learning, Self-Supervised Learning, Active Learning, Uncertainty Sampling, Algorithm Scheduling, Ensemble Construction