3 papers
cs.AI2026
SEER: Supervised Learning to Control Energetic Reasoning
Sascha Van Cauwelaert, Michele Lombardi, Pierre Schaus
One of the main strengths of Constraint Programming is the ability to reduce the search space via propagation. However, propagation is a double-edged sword, with more pruning power…
cs.LG2026
Anytime Optimal Decision Tree Learning with Continuous Features
Harold Kiossou, Pierre Schaus, Siegfried Nijssen
In recent years, significant progress has been made on algorithms for learning optimal decision trees, primarily in the context of binary features. Extending these methods to conti…
cs.AI2025
A Generic Complete Anytime Beam Search for Optimal Decision Tree
Harold Silvère Kiossou, Siegfried Nijssen, Pierre Schaus
Finding an optimal decision tree that minimizes classification error is known to be NP-hard. While exact algorithms based on MILP, CP, SAT, or dynamic programming guarantee optimal…