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Kernel $ε$-Greedy for Contextual Bandits
We also show that for any choice of kernel and the corresponding RKHS, we achieve a sub-linear regret rate depending on the intrinsic dimensionality of the RKHS.
Adaptive estimation of a function from its Exponential Radon Transform in presence of noise
In this article we propose a locally adaptive strategy for estimating a function from its Exponential Radon Transform (ERT) data, without prior knowledge of the smoothness of functions that are to be estimated.
To update or not to update? Delayed Nonparametric Bandits with Randomized Allocation
In randomized strategies, the extent of exploration-exploitation is controlled by a user-determined exploration probability sequence.
Randomized Allocation with Nonparametric Estimation for Contextual Multi-Armed Bandits with Delayed Rewards
We study a multi-armed bandit problem with covariates in a setting where there is a possible delay in observing the rewards.
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