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Off-Policy Evaluation: Why Importance Sampling Gives Unbiased Estimates You Cannot Trust

Off-Policy Evaluation: Why Importance Sampling Gives Unbiased Estimates You Cannot Trust You have logs from a recommendation system that served one ranking policy, and you want to know how a different policy would have performed. You cannot run the new policy yet. You have no A/B test. All you have…

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  1. 2026-11-08 01:31 · DEV Community — Machine Learning
    Off-Policy Evaluation: Why Importance Sampling Gives Unbiased Estimates You Cannot Trust

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