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§4.5, proof of Theorem 4.4, p. 307 — third term: (∇f(y_{t+1}) − ∇f(x_t))⊤(y_{t+1} − x_{t+1}) ≤ (β/2)‖y_{t+1} − x_t‖² + (β/2)‖y_{t+1} − x_{t+1}‖²

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ConvexOptAlg.MirrorProx.thm_4_4_third_term

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

convex-optimizationmirror-proxp2o-batch-pfp2ap2o-gran-per-chapterp2o-plan-bookp2o-v1smoothness

In the setting of Chapter 4, let fff be β\betaβ-smooth on X\mathcal XX with respect to ∥⋅∥\|\cdot\|∥⋅∥, i.e. ∥∇f(x)−∇f(y)∥∗≤β∥x−y∥\|\nabla f(x)-\nabla f(y)\|_*\le\beta\|x-y\|∥∇f(x)−∇f(y)∥∗​≤β∥x−y∥ for x,y∈Xx,y\in\mathcal Xx,y∈X, and let (xt,yt,yt′,xt′)(x_t,y_t,y'_t,x'_t)(xt​,yt​,yt′​,xt′​) be a run of mirror prox with step size η\etaη. Then for every t≥1t\ge1t≥1,

(∇f(yt+1)−∇f(xt))⊤(yt+1−xt+1)≤∥∇f(yt+1)−∇f(xt)∥∗⋅∥yt+1−xt+1∥≤β∥yt+1−xt∥⋅∥yt+1−xt+1∥≤β2∥yt+1−xt∥2+β2∥yt+1−xt+1∥2.\begin{aligned} (\nabla f(y_{t+1})-\nabla f(x_t))^\top(y_{t+1}-x_{t+1}) &\le\|\nabla f(y_{t+1})-\nabla f(x_t)\|_*\cdot\|y_{t+1}-x_{t+1}\|\\ &\le\beta\|y_{t+1}-x_t\|\cdot\|y_{t+1}-x_{t+1}\|\\ &\le\frac\beta2\|y_{t+1}-x_t\|^2+\frac\beta2\|y_{t+1}-x_{t+1}\|^2 . \end{aligned}(∇f(yt+1​)−∇f(xt​))⊤(yt+1​−xt+1​)​≤∥∇f(yt+1​)−∇f(xt​)∥∗​⋅∥yt+1​−xt+1​∥≤β∥yt+1​−xt​∥⋅∥yt+1​−xt+1​∥≤2β​∥yt+1​−xt​∥2+2β​∥yt+1​−xt+1​∥2.​

This bounds the third of the three terms in the proof of Theorem 4.4, by the Cauchy–Schwarz inequality for the dual pairing, β\betaβ-smoothness, and 2ab≤a2+b22ab\le a^2+b^22ab≤a2+b2.

Formalization Note The chain is stated as three inequalities. The dual norm ∥⋅∥∗\|\cdot\|_*∥⋅∥∗​ is the operator norm of a continuous linear functional. No sign condition on β\betaβ is assumed: it is forced by the smoothness inequality whenever X\mathcal XX has two points, and all terms vanish otherwise.

Preamble
import Mathlib
import Definitions.Def_ConvexOptAlg_MirrorProx_Defs
Formal statement
namespace ConvexOptAlg.MirrorProx

/-- The third term in the proof of Theorem 4.4 (Bubeck, arXiv:1405.4980v2, §4.5, p. 307, second
display): for a run of mirror prox with step size `η` on a function `f` that is `β`-smooth on `X`
w.r.t. `‖·‖` (gradient map `f'`), and every `t ≥ 1`,
`(∇f(y_{t+1}) − ∇f(x_t))⊤(y_{t+1} − x_{t+1}) ≤ ‖∇f(y_{t+1}) − ∇f(x_t)‖∗ · ‖y_{t+1} − x_{t+1}‖`,
`‖∇f(y_{t+1}) − ∇f(x_t)‖∗ · ‖y_{t+1} − x_{t+1}‖ ≤ β‖y_{t+1} − x_t‖ · ‖y_{t+1} − x_{t+1}‖`, and
`β‖y_{t+1} − x_t‖ · ‖y_{t+1} − x_{t+1}‖ ≤ (β/2)‖y_{t+1} − x_t‖² + (β/2)‖y_{t+1} − x_{t+1}‖²`.
The dual norm `‖·‖∗` is the operator norm on `E →L[ℝ] ℝ`. -/
theorem thm_4_4_third_term {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
    [FiniteDimensional ℝ E]
    (X D : Set E) (hXc : IsCompact X) (hXconv : Convex ℝ X) (hXD : X ⊆ closure D)
    (hXDne : (X ∩ D).Nonempty)
    (Φ : E → ℝ) (Φ' : E → E →L[ℝ] ℝ) (hΦ : IsMirrorMap D Φ Φ')
    (f : E → ℝ) (f' : E → E →L[ℝ] ℝ) (β : ℝ) (hsm : IsSmoothWRT X f f' β)
    (η : ℝ) (x y y' x' : ℕ → E)
    (hrun : IsMirrorProxRun X D Φ Φ' f' η x y y' x')
    (t : ℕ) (ht : 1 ≤ t) :
    (f' (y (t + 1)) - f' (x t)) (y (t + 1) - x (t + 1))
        ≤ ‖f' (y (t + 1)) - f' (x t)‖ * ‖y (t + 1) - x (t + 1)‖ ∧
      ‖f' (y (t + 1)) - f' (x t)‖ * ‖y (t + 1) - x (t + 1)‖
        ≤ β * ‖y (t + 1) - x t‖ * ‖y (t + 1) - x (t + 1)‖ ∧
      β * ‖y (t + 1) - x t‖ * ‖y (t + 1) - x (t + 1)‖
        ≤ β / 2 * ‖y (t + 1) - x t‖ ^ 2 + β / 2 * ‖y (t + 1) - x (t + 1)‖ ^ 2 := by sorry

end ConvexOptAlg.MirrorProx
Source
Bubeck, arXiv:1405.4980v2, §4.5, proof of Theorem 4.4, p. 307, second display

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