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This paper isolates what produces that optimum and maps where it holds, entirely in simulation, and shows no rotation family can attribute the trend (a compact-group identity).
Training data for machine learning is routinely collected by a selection process the model never sees: loans are observed only when granted, outcomes only when a test was ordered. The standard fixes -- importance weighting, covariate-shift correction, MAR imputation -- assume selection is ignorable given observables. E...
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