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(23) and the next display, p. 35 — summed decrease: F(β⁽¹⁾) − F(β⁽ᴹ⁺¹⁾) ≥ M(L − L₀)/2 · min ‖β⁽ᵐ⁺¹⁾ − β⁽ᵐ⁾‖²

Proved
SubsetShrink.DFO.eq_23

by mikedeng1 · Oct 15, 2026 · Mathlib 0df444a (Lean v4.33.1)

convergence-ratefirst-order-methodsp2o-batch-pfp2ap2o-gran-per-chapterp2o-plan-paperp2o-v1

Let f:Rp→Rf:\mathbb R^p\to\mathbb Rf:Rp→R be differentiable and convex with L0L_0L0​-Lipschitz gradient, L0≥0L_0\ge0L0​≥0, let L>L0L>L_0L>L0​, λ∈R\lambda\in\mathbb Rλ∈R, q∈{1,2}q\in\{1,2\}q∈{1,2}, k≥1k\ge1k≥1, put F(β)=f(β)+λ∥β∥qF(\beta)=f(\beta)+\lambda\|\beta\|_qF(β)=f(β)+λ∥β∥q​, and let β(1),β(2),…\beta^{(1)},\beta^{(2)},\dotsβ(1),β(2),… be a sequence generated by the DFO algorithm (14). Then for every M≥1M\ge1M≥1,

∑m=1M(F(β(m))−F(β(m+1)))≥L−L02∑m=1M∥β(m+1)−β(m)∥22(23)\sum_{m=1}^M\big(F(\beta^{(m)})-F(\beta^{(m+1)})\big)\ge\frac{L-L_0}2\sum_{m=1}^M\|\beta^{(m+1)}-\beta^{(m)}\|_2^2 \tag{23}m=1∑M​(F(β(m))−F(β(m+1)))≥2L−L0​​m=1∑M​∥β(m+1)−β(m)∥22​(23)

and

F(β(1))−F(β(M+1))≥M(L−L0)2min⁡m=1,…,M∥β(m+1)−β(m)∥22.F(\beta^{(1)})-F(\beta^{(M+1)})\ge\frac{M(L-L_0)}2\min_{m=1,\dots,M}\|\beta^{(m+1)}-\beta^{(m)}\|_2^2 .F(β(1))−F(β(M+1))≥2M(L−L0​)​m=1,…,Mmin​∥β(m+1)−β(m)∥22​.

These two displays turn the one-step decrease (22) into the finite-time rate of Proposition 2(b).

Formalization Note The minimum over m=1,…,Mm=1,\dots,Mm=1,…,M is Finset.inf' over Finset.Icc 1 M, which is nonempty because M≥1M\ge1M≥1.

Preamble
import Mathlib
import Definitions.Def_SubsetShrink_DFO_Model
Formal statement
namespace SubsetShrink.DFO

/-- (23) and the display after it, p. 35 (Mazumder, Radchenko & Dedieu, arXiv:1708.03288v4).
Let `f : ℝᵖ → ℝ` be differentiable and convex with `L₀`-Lipschitz gradient ((8)), `L > L₀`,
`L > 0`, `q ∈ {1, 2}`, `k ≥ 1`, and let `β⁽¹⁾, β⁽²⁾, …` be a sequence generated by the DFO
algorithm. For every `M ≥ 1`,
`∑_{m=1}^M (F(β⁽ᵐ⁾) − F(β⁽ᵐ⁺¹⁾)) ≥ ((L − L₀)/2) ∑_{m=1}^M ‖β⁽ᵐ⁺¹⁾ − β⁽ᵐ⁾‖₂²` and
`F(β⁽¹⁾) − F(β⁽ᴹ⁺¹⁾) ≥ (M(L − L₀)/2) min_{m=1,…,M} ‖β⁽ᵐ⁺¹⁾ − β⁽ᵐ⁾‖₂²`. -/
theorem eq_23 {p : ℕ} (f : E p → ℝ) (L0 L lam : ℝ) (q k : ℕ)
    (hq : q = 1 ∨ q = 2) (hk : 1 ≤ k)
    (hdiff : Differentiable ℝ f) (hconv : ConvexOn ℝ Set.univ f) (hL0nn : 0 ≤ L0)
    (hL0 : ∀ β α : E p, ‖gradient f β - gradient f α‖ ≤ L0 * ‖β - α‖)
    (hL : L0 < L) (hLpos : 0 < L)
    (β : ℕ → E p) (hrun : IsDFORun f L lam q k β)
    (M : ℕ) (hM : 1 ≤ M) :
    (L - L0) / 2 * ∑ m ∈ Finset.Icc 1 M, ‖β (m + 1) - β m‖ ^ 2 ≤
        ∑ m ∈ Finset.Icc 1 M, (F f lam q (β m) - F f lam q (β (m + 1))) ∧
    (M : ℝ) * (L - L0) / 2 *
        (Finset.Icc 1 M).inf' (Finset.nonempty_Icc.2 hM) (fun m => ‖β (m + 1) - β m‖ ^ 2) ≤
      F f lam q (β 1) - F f lam q (β (M + 1)) := by sorry

end SubsetShrink.DFO
Source
Mazumder, Radchenko & Dedieu, Subset Selection with Shrinkage, arXiv:1708.03288v4, p. 35, proof of Proposition 2(b) (A.1), (23) and the display after it
Human review
  • Endorsed by Shuze Chen · Oct 15, 2026

    Confirmed by the moderator at approval.

  • Endorsed by mikedeng1 · Oct 15, 2026

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

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