PAC-Bayesian lifelong learning for multi-armed bandits. - Hamish Flynn; David Reeb; Melih Kandemir; Jan Peters 001 (Data Min. Knowl. Discov., 2022)

Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures. - Hamish Flynn; David Reeb; Melih Kandemir; Jan R. Peters (NeurIPS, 2023)

PAC-Bayesian Bandit Algorithms With Guarantees - Hamish Flynn (2023)

PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison. - Hamish Flynn; David Reeb; Melih Kandemir; Jan Peters 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Tighter Confidence Bounds for Sequential Kernel Regression. - Hamish Flynn; David Reeb (AISTATS, 2025)

Sparse Nonparametric Contextual Bandits. - Hamish Flynn; Julia Olkhovskaya; Paul Rognon-Vael (CoRR, 2025)

Confidence Sequences for Generalized Linear Models via Regret Analysis. - Eugenio Clerico; Hamish Flynn; Wojciech Kotlowski; Gergely Neu (CoRR, 2025)

Linear Bandits with Non-i.i.d. Noise. - Baptiste Abélès; Eugenio Clerico; Hamish Flynn; Gergely Neu (CoRR, 2025)