Proposition 5, second sentence — a unique mean-optimal decision minimizes SPO risk
ProvedSmartPTO.Fisher.prop5_conversebayes-riskoptimal-decisionsp2o-batch-pfp2ap2o-gran-per-chapterp2o-plan-paperp2o-v1spo-loss
Let be an integrable probability law on , with mean , and let be a nonempty compact convex feasible set. Suppose the prediction has a singleton optimal-decision set and that this set is contained in . Then, for every prediction ,
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 .
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
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.