Offline Coverage for a Contextual Gaussian-Process Rule
Abstract
Offline rate analysis and contextual Gaussian-process selection share the need to prepare evidence before covariates are observed in use. Validation should freeze that preparation and hold out meaningful contexts. Independent local checks distinguish direct coverage from borrowing. Later application outcomes may support an updated policy but cannot retrospectively justify the original offline rule. This focused synthesis develops an empirical comparison that preserves the terminal action, observation process, and total verification cost. Its proposed tests are prospective; no new simulation run, model-training result, or intervention effect is reported.
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