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Found 3 papers, 2 papers with code
Cross-Validated Off-Policy Evaluation
In this paper, we study the problem of estimator selection and hyper-parameter tuning in off-policy evaluation.
Learning Action Embeddings for Off-Policy Evaluation
Off-policy evaluation (OPE) methods allow us to compute the expected reward of a policy by using the logged data collected by a different policy.
Pessimistic Off-Policy Optimization for Learning to Rank
Off-policy learning is a framework for optimizing policies without deploying them, using data collected by another policy.
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