36 citations · 59 across the 7 of their papers we have counts for
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cs.LG2025
Sharing Knowledge without Sharing Data: Stitches can improve ensembles of disjointly trained models
Arthur Guijt, Dirk Thierens, Ellen Kerkhof +3
Deep learning has been shown to be very capable at performing many real-world tasks. However, this performance is often dependent on the presence of large and varied datasets. In s…
cs.LG2021★ 20 cited
EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions
Laurens Bliek, Arthur Guijt, Rickard Karlsson +2
Surrogate algorithms such as Bayesian optimisation are especially designed for black-box optimisation problems with expensive objectives, such as hyperparameter tuning or simulatio…