Incremental permutation feature importance (iPFI): towards online explanations on data streams
F. Fumagalli, M. Muschalik, E. Hüllermeier, B. Hammer, Machine Learning (2023).

Incremental permutation feature importance (iPFI): towards online explanations on data streams
F. Fumagalli, M. Muschalik, E. Hüllermeier, B. Hammer, Machine Learning 112 (2023) 4863–4903.

On testing transitivity in online preference learning
B. Haddenhorst, V. Bengs, E. Hüllermeier, Machine Learning (2021) 2063–2084.

MODES: model-based optimization on distributed embedded systems
J. Shi, J. Bian, J. Richter, K.-H. Chen, J. Rahnenführer, H. Xiong, J.-J. Chen, Machine Learning 110 (2021) 1527–1547.

On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis
V. Melnikov, E. Hüllermeier, Machine Learning (2018).