Active Exploration in Markov Decision Processes. - Jean Tarbouriech; Alessandro Lazaric (AISTATS, 2019)

No-Regret Exploration in Goal-Oriented Reinforcement Learning. - Jean Tarbouriech; Evrard Garcelon; Michal Valko; Matteo Pirotta; Alessandro Lazaric (ICML, 2020)

Adversarial Attacks on Linear Contextual Bandits. - Evrard Garcelon; Baptiste Rozière; Laurent Meunier; Jean Tarbouriech; Olivier Teytaud; Alessandro Lazaric; Matteo Pirotta (NeurIPS, 2020)

Improved Sample Complexity for Incremental Autonomous Exploration in MDPs. - Jean Tarbouriech; Matteo Pirotta; Michal Valko; Alessandro Lazaric (NeurIPS, 2020)

Active Model Estimation in Markov Decision Processes. - Jean Tarbouriech; Shubhanshu Shekhar; Matteo Pirotta; Mohammad Ghavamzadeh; Alessandro Lazaric (UAI, 2020)

Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model. - Jean Tarbouriech; Matteo Pirotta; Michal Valko; Alessandro Lazaric (ALT, 2021)

A Provably Efficient Sample Collection Strategy for Reinforcement Learning. - Jean Tarbouriech; Matteo Pirotta; Michal Valko; Alessandro Lazaric (NeurIPS, 2021)

Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret. - Jean Tarbouriech; Runlong Zhou; Simon S. Du; Matteo Pirotta; Michal Valko; Alessandro Lazaric (NeurIPS, 2021)

Adaptive Multi-Goal Exploration. - Jean Tarbouriech; Omar Darwiche Domingues; Pierre Ménard; Matteo Pirotta; Michal Valko; Alessandro Lazaric (AISTATS, 2022)

Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching. - Pierre-Alexandre Kamienny; Jean Tarbouriech; Sylvain Lamprier; Alessandro Lazaric; Ludovic Denoyer (ICLR, 2022)

Goal-oriented exploration for reinforcement learning. (Exploration d'états buts pour l'apprentissage par renforcement). - Jean Tarbouriech (2022)

Probabilistic Inference in Reinforcement Learning Done Right. - Jean Tarbouriech; Tor Lattimore; Brendan O'Donoghue (NeurIPS, 2023)