Argmin consistency under uniform convergence in probability

On a compact parameter set, a continuous deterministic objective with a unique minimum has a positive separation gap outside each neighbourhood of its minimizer. Uniform convergence in probability of the random objectives bounds the deterministic objective difference at any attained random minimizer by twice the supremum discrepancy. This proves statistical consistency of each measurable minimizing selection.