no code implementations • 19 Mar 2024 • Hamish Flynn, David Reeb
In this capacity, they can inform the exploration-exploitation trade-off and form a core component in many sequential learning and decision-making algorithms.
no code implementations • 29 Nov 2022 • Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
On the one hand, we found that PAC-Bayes bounds are a useful tool for designing offline bandit algorithms with performance guarantees.
no code implementations • 7 Mar 2022 • Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
We present a PAC-Bayesian analysis of lifelong learning.