3 papers
cs.LG2026
RegKT: Interpretable and Robust Deep Knowledge Tracing With IRT-Regularizer
Samuel Girard, Juan D. Pinto, Jill-Jênn Vie +1
As deep learning models continue to advance, knowledge tracing models have achieved higher accuracy. However, these gains come at the cost of reduced interpretability, which is cru…
cs.LG2026
Counterfactual learning of new adaptive instructional policies using logged data
Samuel Girard, Sein Minn, Amel Bouzeghoub +1
Optimizing instructional policies in Intelligent Tutoring Systems (ITS) typically requires costly online experimentation or student simulators that may fail to capture real-world d…
stat.ML2025
Fast Best-in-Class Regret for Contextual Bandits
Samuel Girard, Aurelien Bibaut, Arthur Gretton +2
We study the problem of stochastic contextual bandits in the agnostic setting, where the goal is to compete with the best policy in a given class without assuming realizability or…