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ENTITY Weighted importance sampling for off-policy learning with linear function approximation

Weighted importance sampling for off-policy learning with linear function approximation

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  1. RESEARCH · CL_147428 ·

    New Kernel-WIS estimator improves off-policy evaluation for contextual bandits

    Researchers have introduced Kernel-WIS, a new estimator for off-policy evaluation in contextual bandits. This method utilizes offline data and is designed to be asymptotically consistent. Kernel-WIS aims to outperform e…