Theorem 4.3 — mixed regularity gives linear contraction
ProvedRelaxedPRS.Linear.theorem_4_3convex-optimizationlinear-convergencep2o-batch-pfp2ap2o-gran-per-chapterp2o-plan-paperp2o-v1relaxed-peaceman-rachford
Let be proper closed convex functions on a real Hilbert space. Let , let follow relaxed PRS with , and let be a fixed point of . Suppose either has a -Lipschitz gradient and is -strongly convex, or has that gradient regularity and is -strongly convex, with . Define
In each of the two cases, for all ,
This is the paper's mixed-regularity linear contraction theorem, covering both readings of “respectively.”
Preamble
import Mathlib import Definitions.Def_RelaxedPRS_Linear_Setting
Formal statement
namespace RelaxedPRS.Linear
/-- Theorem 4.3, p. 16: linear contraction when regularity is split across f and g. -/
theorem theorem_4_3 {H : Type*} [NormedAddCommGroup H] [InnerProductSpace ℝ H] [CompleteSpace H]
(f g : H → EReal)
(hf : ThreeOpSplitting.ConvexRates.IsProperClosedConvex f)
(hg : ThreeOpSplitting.ConvexRates.IsProperClosedConvex g)
(γ : ℝ) (hγ : 0 < γ) (Pf Pg : H → H)
(hPf : ThreeOpSplitting.ConvexRates.IsProx γ f Pf)
(hPg : ThreeOpSplitting.ConvexRates.IsProx γ g Pg)
(lam : ℕ → ℝ) (hlam : ∀ k, 0 < lam k ∧ lam k ≤ 1)
(z : ℕ → H) (hz : RelaxedPRS.StrongCvx.IsPRSRun Pf Pg lam z)
(zs : H) (hzs : RelaxedPRS.StrongCvx.TPRS Pf Pg zs = zs)
(μ β : ℝ) (hμ : 0 < μ) (hβ : 0 < β) :
(RelaxedPRS.StrongCvx.HasLipGrad β g → RelaxedPRS.StrongCvx.IsStrongCvxE μ f →
∀ k, ‖z (k + 1) - zs‖ ≤ C43 γ μ β (lam k) * ‖z k - zs‖) ∧
(RelaxedPRS.StrongCvx.HasLipGrad β f → RelaxedPRS.StrongCvx.IsStrongCvxE μ g →
∀ k, ‖z (k + 1) - zs‖ ≤ C43 γ μ β (lam k) * ‖z k - zs‖) := by sorry
end RelaxedPRS.Linear
Source
Davis & Yin, Faster convergence rates of relaxed Peaceman-Rachford and ADMM under regularity assumptions, arXiv:1407.5210v3, p. 16, Theorem 4.3
Human review
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.