4 citations · 17 across the 7 of their papers we have counts for
8 papers
Computing Abductive Explanations for Boosted Trees
Gilles Audemard, Jean-Marie Lagniez, Pierre Marquis +1
Boosted trees is a dominant ML model, exhibiting high accuracy. However, boosted trees are hardly intelligible, and this is a problem whenever they are used in safety-critical appl…
Proceedings of the 2022 XCSP3 Competition
Gilles Audemard, Christophe Lecoutre, Emmanuel Lonca
This document represents the proceedings of the 2022 XCSP3 Competition. The results of this competition of constraint solvers were presented at FLOC (Federated Logic Conference) 20…
On the Explanatory Power of Decision Trees
Gilles Audemard, Steve Bellart, Louenas Bounia +3
Decision trees have long been recognized as models of choice in sensitive applications where interpretability is of paramount importance. In this paper, we examine the computationa…
Trading Complexity for Sparsity in Random Forest Explanations
Gilles Audemard, Steve Bellart, Louenas Bounia +3
Random forests have long been considered as powerful model ensembles in machine learning. By training multiple decision trees, whose diversity is fostered through data and feature…
On the Computational Intelligibility of Boolean Classifiers
Gilles Audemard, Steve Bellart, Louenas Bounia +3
In this paper, we investigate the computational intelligibility of Boolean classifiers, characterized by their ability to answer XAI queries in polynomial time. The classifiers und…
XCSP3-core: A Format for Representing Constraint Satisfaction/Optimization Problems
Frédéric Boussemart, Christophe Lecoutre, Gilles Audemard +1
In this document, we introduce XCSP3-core, a subset of XCSP3 that allows us to represent constraint satisfaction/optimization problems. The interest of XCSP3-core is multiple: (i)…
SAT Heritage: a community-driven effort for archiving, building and running more than thousand SAT solvers
Gilles Audemard, Loïc Paulevé, Laurent Simon
SAT research has a long history of source code and binary releases, thanks to competitions organized every year. However, since every cycle of competitions has its own set of rules…
Integrating Conflict Driven Clause Learning to Local Search
Gilles Audenard, Jean-Marie Lagniez, Bertrand Mazure +1
This article introduces SatHyS (SAT HYbrid Solver), a novel hybrid approach for propositional satisfiability. It combines local search and conflict driven clause learning (CDCL) sc…