14 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre de Recherche en Informatique, Signal et Automatique de LilleFR11 papers
- Université de LilleFR11 papers
- Centre de Recherche en InformatiqueFR9 papers
- Centre National de la Recherche ScientifiqueFR5 papers
- Centre Inria de l'Université de LilleFR2 papers
- École Centrale de LilleFR2 papers
- Institut national de recherche en sciences et technologies du numériqueFR2 papers
- Laboratoire d'Informatique, de Robotique et de Microélectronique de MontpellierFR2 papers
- Brno University of TechnologyCZ1 paper
- CentraleSupélecFR1 paper
- Centrum Wiskunde & InformaticaNL1 paper
- College of Western IdahoUS1 paper
3 papers · 1 filter
How Hard is it to Confuse a World Model?
Waris Radji, Odalric-Ambrym Maillard
In reinforcement learning (RL) theory, the concept of most confusing instances is central to establishing regret lower bounds, that is, the minimal exploration needed to solve a pr…
The Confusing Instance Principle for Online Linear Quadratic Control
Waris Radji, Odalric-Ambrym Maillard
We revisit the problem of controlling linear systems with quadratic cost under unknown dynamics with model-based reinforcement learning. Traditional methods like Optimism in the Fa…
Optimal Interpretability-Performance Trade-off of Classification Trees with Black-Box Reinforcement Learning
Hector Kohler, Riad Akrour, Philippe Preux
Interpretability of AI models allows for user safety checks to build trust in these models. In particular, decision trees (DTs) provide a global view on the learned model and clear…