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A General $\widetildeΩ(\sqrt{T γ_T})$ Lower Bound for Kernel Bandits
The kernel bandit problem consists of sequentially optimizing an unknown function with noisy feedback, where the function has bounded norm in a given Reproducing Kernel Hilbert Space (RKHS). A central quantity in the regret analysis of kernel bandits is the maximum information gain $γ_T$. In particu
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