5 citations
- Laboratoire d'Analyse et d'Architecture des SystèmesFR5 papers
- École de Technologie SupérieureCA4 papers
- Université du Québec à MontréalCA3 papers
- Polytechnique MontréalCA2 papers
- Université Fédérale de Toulouse Midi-PyrénéesFR2 papers
- Centre National de la Recherche ScientifiqueFR1 paper
- Électricité de France (France)FR1 paper
- Institut National Polytechnique de ToulouseFR1 paper
- Laboratoire des Sciences pour la Conception, l'Optimisation et la ProductionFR1 paper
- LIP6FR1 paper
- Osiris Therapeutics (United States)US1 paper
9 papers
An iterative Constraint Programming approach to integrate maximum workload constraints in preemptive jobshop scheduling
Tanguy Terrien, Cyrille Briand
Optimizing schedules in real-world settings often requires considering workload constraints, specially for human resources, to ensure regulatory compliance, impose rest periods, or…
Solving a large oral examination timetabling problem using a multidimensional knapsack MILP formulation
Cyrille Briand, Jean-Pierre Belaud
This paper addresses the Oral Examination Timetabling Problem (OETP) for France's prestigious engineering schools, an organization managed by the Service des Concours Communs Polyt…
BORWin: Exact algorithm based on a Bi-Objective Relaxation for Window-constrained problems
Christian Artigues, Pascale Bendotti, Alexandre Heintzmann +2
A mixed integer maximization problem involving several additional constraints defined with both a lower and an upper bound is considered. It is assumed that one of such constraints…
Smooth Sensitivity for Learning Differentially-Private yet Accurate Rule Lists
Timothée Ly, Julien Ferry, Marie-José Huguet +2
Differentially-private (DP) mechanisms can be embedded into the design of a machine learning algorithm to protect the resulting model against privacy leakage. However, this often c…
SoK: Taming the Triangle -- On the Interplays between Fairness, Interpretability and Privacy in Machine Learning
Julien Ferry, Ulrich Aïvodji, Sébastien Gambs +2
Machine learning techniques are increasingly used for high-stakes decision-making, such as college admissions, loan attribution or recidivism prediction. Thus, it is crucial to ens…
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…