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Proposition 5, second sentence — a unique mean-optimal decision minimizes SPO risk

Proved
SmartPTO.Fisher.prop5_converse

by mikedeng1 · Oct 6, 2026 · Mathlib 0df444a (Lean v4.33.1)

bayes-riskoptimal-decisionsp2o-batch-pfp2ap2o-gran-per-chapterp2o-plan-paperp2o-v1spo-loss

Let PPP be an integrable probability law on Rd\mathbb R^dRd, with mean cˉ=EP[c]\bar c=\mathbb E_P[c]cˉ=EP​[c], and let SSS be a nonempty compact convex feasible set. Suppose the prediction c∗c^*c∗ has a singleton optimal-decision set W∗(c∗)W^*(c^*)W∗(c∗) and that this set is contained in W∗(cˉ)W^*(\bar c)W∗(cˉ). Then, for every prediction c^\hat cc^,

RSPO(c∗)≤RSPO(c^).R_{\mathrm{SPO}}(c^*)\le R_{\mathrm{SPO}}(\hat c).RSPO​(c∗)≤RSPO​(c^).

Thus a prediction whose unique selected decision optimizes mean cost minimizes the true SPO risk.

Formalization Note This uses the unambiguous loss of Definition 2 and imposes no symmetry or continuity on PPP.

Preamble
import Mathlib
import Definitions.Def_SPOBounds_Natarajan_Model
import Definitions.Def_SmartPTO_Fisher_Setting

open scoped InnerProductSpace
open MeasureTheory ProbabilityTheory
Formal statement
namespace SmartPTO.Fisher

/-- Proposition 5, second sentence, p. 22. -/
theorem prop5_converse {d : ℕ} (S : Set (EuclideanSpace ℝ (Fin d)))
    (hSne : S.Nonempty) (hScpt : IsCompact S) (hScvx : Convex ℝ S)
    (P : Measure (EuclideanSpace ℝ (Fin d))) [IsProbabilityMeasure P]
    (hInt : Integrable id P) (cstar : EuclideanSpace ℝ (Fin d))
    (hSingle : ∃ w, Wstar S cstar = {w})
    (hSub : Wstar S cstar ⊆ Wstar S (∫ c, c ∂P)) :
    ∀ chat : EuclideanSpace ℝ (Fin d), spoRisk S P cstar ≤ spoRisk S P chat := by sorry

end SmartPTO.Fisher
Source
Elmachtoub & Grigas, Smart "Predict, then Optimize", arXiv:1710.08005v5, p. 22, Proposition 5, second sentence; §4.1 p. 22
Human review
  • Endorsed by Shuze Chen · Oct 6, 2026

    Confirmed by the moderator at approval.

  • Endorsed by mikedeng1 · Oct 6, 2026

    Confirmed by the mission captain (proposal self-audit).

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