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§3.1, proof of Theorem 3.2, p. 265 — f(x_s) − f(x*) ≤ (‖x_s − x*‖² − ‖y_{s+1} − x*‖²)/(2η) + (η/2)‖g_s‖²

Proved
ConvexOptAlg.Subgradient.thm_3_2_step

by mikedeng1 · Oct 5, 2026 · Mathlib 0df444a (Lean v4.33.1)

convex-optimizationp2o-batch-pfp2ap2o-gran-per-chapterp2o-plan-bookp2o-v1subgradient-method

Let X⊆Rn\mathcal X\subseteq\mathbb R^nX⊆Rn and f:Rn→Rf:\mathbb R^n\to\mathbb Rf:Rn→R, and let (xs),(gs)(x_s),(g_s)(xs​),(gs​) be a run of projected subgradient descent on fff over X\mathcal XX with step sizes (ηs)(\eta_s)(ηs​) for the steps 1,…,T1,\dots,T1,…,T. Let x∗∈Xx^*\in\mathcal Xx∗∈X, let 1≤s≤T1\le s\le T1≤s≤T with η=ηs>0\eta=\eta_s>0η=ηs​>0, and put ys+1=xs−ηgsy_{s+1}=x_s-\eta g_sys+1​=xs​−ηgs​. Then

f(xs)−f(x∗)≤12η(∥xs−x∗∥2−∥ys+1−x∗∥2)+η2∥gs∥2.f(x_s)-f(x^*)\le\frac{1}{2\eta}\Big(\|x_s-x^*\|^2-\|y_{s+1}-x^*\|^2\Big)+\frac{\eta}{2}\|g_s\|^2 .f(xs​)−f(x∗)≤2η1​(∥xs​−x∗∥2−∥ys+1​−x∗∥2)+2η​∥gs​∥2.

This is the one-step inequality from which the rate of Theorem 3.2 is obtained by summation.

Formalization Note The page states the inequality for a constant step η\etaη; it is stated here for the step ηs\eta_sηs​ used at step sss, which contains the constant case. Only x∗∈Xx^*\in\mathcal Xx∗∈X is needed, not that x∗x^*x∗ is a minimizer. The positivity η>0\eta>0η>0 is the page's standing condition on a step size.

Preamble
import Mathlib
import Definitions.Def_OnlineConvexOpt_FirstOrder_Protocol
import Definitions.Def_ConvexOptAlg_Subgradient_Defs
Formal statement
namespace ConvexOptAlg.Subgradient

/-- Bubeck, proof of Theorem 3.2, p. 265, first display (first and last members): for a run of
projected subgradient descent and a step `1 ≤ s ≤ T` with `η s > 0`, writing
`y_{s+1} = x s - η s • g s`,
`f(x_s) - f(x*) ≤ (1/(2η))(‖x_s - x*‖² - ‖y_{s+1} - x*‖²) + (η/2)‖g_s‖²`. -/
theorem thm_3_2_step {n : ℕ} (X : Set (EuclideanSpace ℝ (Fin n)))
    (f : EuclideanSpace ℝ (Fin n) → ℝ) (η : ℕ → ℝ) (x g : ℕ → EuclideanSpace ℝ (Fin n))
    (T : ℕ) (hrun : IsProjSubgradRun X f η x g T) (xstar : EuclideanSpace ℝ (Fin n))
    (hxstar : xstar ∈ X) (s : ℕ) (hs1 : 1 ≤ s) (hsT : s ≤ T) (hη : 0 < η s) :
    f (x s) - f xstar ≤
      1 / (2 * η s) * (‖x s - xstar‖ ^ 2 - ‖(x s - η s • g s) - xstar‖ ^ 2)
        + η s / 2 * ‖g s‖ ^ 2 := by sorry

end ConvexOptAlg.Subgradient
Source
Bubeck, arXiv:1405.4980v2, §3.1, proof of Theorem 3.2, p. 265, first display (first and last members)
Human review
  • Endorsed by Shuze Chen · Oct 5, 2026

    Confirmed by the moderator at approval.

  • Endorsed by mikedeng1 · Oct 5, 2026

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

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