 Meanwhile, in the case of penalized kernel regression, we show that our method has a quasi-oracle property , whereby even if our pilot estimates for marginal effects and treatment propensities are not particularly accurate, we achieve the same regret bounds as an oracle who has a-priori knowledge of these  nuisance components.
<fluency>  Meanwhile, in the case of penalized kernel regression, we show that our method has a quasi-oracle property , whereby even if our pilot estimates for marginal effects and treatment propensities are not particularly accurate, we achieve the same regret bounds as an oracle who has a-priori knowledge of these  nuisance components.
 Meanwhile, in the case of penalized kernel regression, we show that our method has a quasi-oracle property , whereby even if our pilot estimates for marginal effects and treatment propensities are not particularly accurate, we achieve the same regret bounds as an oracle who has a priori knowledge of these nuisance components.