7 citations · 13 across the 7 of their papers we have counts for
4 papers · 1 filter
Learning Admissible Heuristics via Cost Partitioning
Hugo Barral, Quentin Cappart, Marie-José Huguet +1
Admissible heuristics are essential for optimal planning, yet learning them remains challenging due to the risk of overestimation. Cost partitioning combines multiple abstraction h…
Probabilistic Dataset Reconstruction from Interpretable Models
Julien Ferry, Ulrich Aïvodji, Sébastien Gambs +2
Interpretability is often pointed out as a key requirement for trustworthy machine learning. However, learning and releasing models that are inherently interpretable leaks informat…
Optimizing Binary Decision Diagrams with MaxSAT for classification
Hao Hu, Marie-José Huguet, Mohamed Siala
The growing interest in explainable artificial intelligence (XAI) for critical decision making motivates the need for interpretable machine learning (ML) models. In fact, due to th…
Constraint programming for planning test campaigns of communications satellites
Emmanuel Hébrard, Marie-José Huguet, Daniel Veysseire +2
The payload of communications satellites must go through a series of tests to assert their ability to survive in space. Each test involves some equipment of the payload to be activ…