A unified algorithm class, Generic-GP, uses scalar exploration distributions to interpolate between UCB and randomized exploration, achieving \tilde O(\gamma_T\sqrt T) regret in kernelized bandits.
On the sublinear regret of GP-UCB
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Efficient kernelized bandit algorithms via exploration distributions
A unified algorithm class, Generic-GP, uses scalar exploration distributions to interpolate between UCB and randomized exploration, achieving \tilde O(\gamma_T\sqrt T) regret in kernelized bandits.