A kernel-interpolation explore-then-commit algorithm achieves sublinear regret in high-dimensional contextual bandits under low-rank context covariance, and sublinear lenient regret under weaker spectral decay.
Kakade, and Matthias W
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High-dimensional Nonparametric Contextual Bandit Problem
A kernel-interpolation explore-then-commit algorithm achieves sublinear regret in high-dimensional contextual bandits under low-rank context covariance, and sublinear lenient regret under weaker spectral decay.