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Linear Ensemble Sampling with Smaller Ensembles
Ensemble sampling offers a practical approach to randomized exploration by maintaining a collection of models, but how small an ensemble can be while retaining strong regret guarantees remains unresolved. In particular, the existing guarantees use an ensemble size of $Θ(d\log T)$, leaving a logarith
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