Luca Pascal Staus — accepted AI-conference papers

2025

Learning Minimum-Size BDDs: Towards Efficient Exact Algorithms

Christian Komusiewicz, Andre Schidler, Frank Sommer, Manuel Sorge, Luca Pascal Staus

ICML 2025poster

Binary decision diagrams (BDDs) are widely applied tools to compactly represent labeled data as directed acyclic graphs; for efficiency and interpretability reasons small BDDs are preferred. Given labeled data, minimizing BDDs is NP-complete and thus recent research focused on the influence of param…

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2025

Witty: An Efficient Solver for Computing Minimum-Size Decision Trees

Luca Pascal Staus, Christian Komusiewicz, Frank Sommer, Manuel Sorge

AAAI 2025technical

Decision trees are a classic model for summarizing and classifying data. To enhance interpretability and generalization properties, it has been proposed to favor small decision trees. Accordingly, in the minimum-size decision tree training problem (MSDT), the input is a set of training examples in…

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