33 citations · 91 across the 14 of their papers we have counts for
19 papers
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…
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…
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…
Decision Diagram-Based Branch-and-Bound with Caching for Dominance and Suboptimality Detection
Vianney Coppé, Xavier Gillard, Pierre Schaus
The branch-and-bound algorithm based on decision diagrams introduced by Bergman et al. in 2016 is a framework for solving discrete optimization problems with a dynamic programming…
Are Travel Bans the Answer to Stopping the Spread of COVID-19 Variants? Lessons from a Multi-Country SIR Model
Frederic Docquier, Nicolas Golenvaux, Pierre Schaus
Detections of mutations of the SARS-CoV-2 virus gave rise to new packages of interventions. Among them, international travel restrictions have been one of the fastest and most visi…
Improving the filtering of Branch-And-Bound MDD solver (extended)
Xavier Gillard, Vianney Coppé, Pierre Schaus +1
This paper presents and evaluates two pruning techniques to reinforce the efficiency of constraint optimization solvers based on multi-valued decision-diagrams (MDD). It adopts the…