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Smoothness in treatment effects unlocks near-optimal policy learning in high-dimensional, low-signal digital experimentation.
Unlock asymptotically normal and semiparametrically efficient estimators in adaptive data collection by using a novel target-specific condition called "directional stability," which is weaker than previous target-agnostic conditions.
