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Variance-Optimal Off-Policy Evaluation with Conjunct Effect Modeling

Nicolò Felicioni et al.
arXiv CS · Papers
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deep-learningmachine-learningneural-networks
Off-policy evaluation (OPE) for contextual bandit policies becomes challenging when action-level importance weighting incurs excessive variance. Doubly robust (DR) estimation remains unbiased under common support but retains these high-variance action-level weights. A prior estimator, Off-policy eva
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