Derives first lower bound on γ_t for mean-based algorithms in unknown-horizon bandit settings, proposes two new algorithms, and shows some are also no-regret.
In Proceedings of the 2018 ACM Conference on Economics and Computation (Ithaca, NY, USA) (EC ’18)
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Mean-based algorithms: A lower bound and regret
Derives first lower bound on γ_t for mean-based algorithms in unknown-horizon bandit settings, proposes two new algorithms, and shows some are also no-regret.