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Publications

Relative Information Gain and Gaussian Process Regression
Hamish Flynn;
Preprint.

Linear Bandits with Non-i.i.d. Noise
Baptiste Abélès, Eugenio Clerico, Hamish Flynn, Gergely Neu;
Preprint.

Confidence Sequences for Generalized Linear Models via Regret Analysis
Eugenio Clerico, Hamish Flynn, Wojciech Kotłowski, Gergely Neu;
Preprint.

Sparse Nonparametric Contextual Bandits
Hamish Flynn, Julia Olkhovskaya, Paul Rognon-Vael;
Preprint.

Sparse Optimistic Information Directed Sampling
Ludovic Schwartz, Hamish Flynn, Gergely Neu;
NeurIPS, 2025.

Uniform Mean Estimation for Monotonic Processes
Eugenio Clerico, Hamish Flynn, Patrick Rebeschini;
Statistics and Probability Letters, 2025.

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

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

PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison
Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters;
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.

PAC-Bayesian Lifelong Learning For Multi-Armed Bandits
Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters;
Data Mining and Knowledge Discovery, 2022.