Multi-Armed Bandit Learning in IoT Networks: Learning Helps Even in Non-stationary Settings. - Rémi Bonnefoi; Lilian Besson; Christophe Moy; Emilie Kaufmann; Jacques Palicot (CrownCom, 2017)

Multi-Player Bandits Models Revisited. - Lilian Besson; Emilie Kaufmann (CoRR, 2017)

{Multi-Player Bandits Revisited}. - Lilian Besson; Emilie Kaufmann (ALT, 2018)

Aggregation of multi-armed bandits learning algorithms for opportunistic spectrum access. - Lilian Besson; Emilie Kaufmann; Christophe Moy (WCNC, 2018)

What Doubling Tricks Can and Can't Do for Multi-Armed Bandits. - Lilian Besson; Emilie Kaufmann (CoRR, 2018)

Decentralized Spectrum Learning for IoT Wireless Networks Collision Mitigation. - Christophe Moy; Lilian Besson (DCOSS, 2019)

GNU Radio Implementation of MALIN: "Multi-Armed bandits Learning for Internet-of-things Networks". - Lilian Besson; Rémi Bonnefoi; Christophe Moy (WCNC, 2019)

Upper-Confidence Bound for Channel Selection in LPWA Networks with Retransmissions. - Rémi Bonnefoi; Lilian Besson; Julio Manco-Vásquez; Christophe Moy (WCNC Workshops, 2019)

The Generalized Likelihood Ratio Test meets klUCB: an Improved Algorithm for Piece-Wise Non-Stationary Bandits. - Lilian Besson; Emilie Kaufmann (CoRR, 2019)

Multi-Players Bandit Algorithms for Internet of Things Networks. (Algorithmes de Bandits Multi-Joueurs pour les Réseaux de l'Internet des Objets). - Lilian Besson (2019)

Decentralized spectrum learning for radio collision mitigation in ultra-dense IoT networks: LoRaWAN case study and experiments. - Christophe Moy; Lilian Besson; Guillaume Delbarre; Laurent Toutain (Ann. des Télécommunications, 2020)

Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits. - Lilian Besson; Emilie Kaufmann; Odalric-Ambrym Maillard; Julien Seznec (J. Mach. Learn. Res., 2022)