When Can You Trust Offline Evaluation of Equal-Cost Top-k Allocation? A Controlled, Reproducible Benchmark and Practitioner's Guide
Organizations decide whom to treat under a budget and want to know what a targeting rule would have earned before deploying it. Off-policy evaluation promises this from logged data, but the deployable rule is a deterministic top-k policy: it removes all averaging over actions, so weak overlap hits the estimate directly. We benchmark six estimators across five datasets and two known-effect sweeps, and validate the mechanisms against a non-simulated paired reference. First, weak overlap is governe
Record details
Published: 12 August 2026
Source: arXiv cs.LG
Category: Research
Topics: Regulation
Retrieved: 14 August 2026
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ethics.ai (12 August 2026), “When Can You Trust Offline Evaluation of Equal-Cost Top-k Allocation? A Controlled, Reproducible Benchmark and Practitioner's Guide,” evidence record 19476, https://ethics.ai/record/19476 (originally published by arXiv cs.LG).
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