State-by-state Minimax Adaptive Estimation for Nonparametric Hidden Markov Models. - Luc Lehéricy (J. Mach. Learn. Res., 2018)

Pair Matching: When bandits meet stochastic block model. - Christophe Giraud 002; Yann Issartel; Luc Lehéricy; Matthieu Lerasle (CoRR, 2019)

Identifiability and Consistent Estimation of Nonparametric Translation Hidden Markov Models with General State Space. - Elisabeth Gassiat; Sylvain Le Corff; Luc Lehéricy (J. Mach. Learn. Res., 2020)

Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA. - Hermanni Hälvä; Sylvain Le Corff; Luc Lehéricy; Jonathan So; Yongjie Zhu; Elisabeth Gassiat; Aapo Hyvärinen (NeurIPS, 2021)

Joint self-supervised blind denoising and noise estimation. - Jean Ollion; Charles Ollion; Elisabeth Gassiat; Luc Lehéricy; Sylvain Le Corff (CoRR, 2021)

On the convergence of the MLE as an estimator of the learning rate in the Exp3 algorithm. - Julien Aubert; Luc Lehéricy; Patricia Reynaud-Bouret (ICML, 2023)

Gradient Ascent Activity-Based Credit Assignment with History-Dependent Reward. - Oussama Sabri; Luc Lehéricy; Alexandre Muzy (BI (1), 2024)

Multi-agent Sequential Learning via Gradient Ascent Credit Assignment. - Oussama Sabri; Luc Lehéricy; Alexandre Muzy (CSAI, 2024)

Identifiability of discrete input-output hidden Markov models with external signals. - Etienne David; Jean Bellot; Sylvain Le Corff; Luc Lehéricy (Stat. Comput., 2024)

Model selection for behavioral learning data and applications to contextual bandits. - Julien Aubert; Louis Köhler; Luc Lehéricy; Giulia Mezzadri; Patricia Reynaud-Bouret (AISTATS, 2025)