(22), p. 35 — one DFO step decreases F by at least (L − L₀)/2 ‖η̂ − β‖²
ProvedSubsetShrink.DFO.eq_22first-order-methodsp2o-batch-pfp2ap2o-gran-per-chapterp2o-plan-paperp2o-v1sufficient-decrease
Let be differentiable and convex with -Lipschitz gradient, , and let with , , , . Put . If and
then
Applied with and , this is the sufficient-decrease inequality of the DFO method, from which both parts of Proposition 2 follow.
Formalization Note No sign condition on or is needed here. is required for the step to be the paper's.
Preamble
import Mathlib import Definitions.Def_SubsetShrink_DFO_Model
Formal statement
namespace SubsetShrink.DFO
/-- (22), p. 35 (Mazumder, Radchenko & Dedieu, arXiv:1708.03288v4). Let `f : ℝᵖ → ℝ` be
differentiable and convex with `L₀`-Lipschitz gradient ((8)), `L ≥ L₀` with `L > 0`,
`q ∈ {1, 2}`, `k ≥ 1`. If `‖β‖₀ ≤ k` and `η̂ ∈ S(β − (1/L)∇f(β); k; (λ/L)ℓ_q)`, then
`F(β) ≥ ((L − L₀)/2)‖η̂ − β‖₂² + F(η̂)`, where `F(β) = f(β) + λ‖β‖_q`. -/
theorem eq_22 {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 ηhat : E p) (hβ : l0 β ≤ k)
(hη : IsThresh (β - (1 / L) • gradient f β) k (lam / L) q ηhat) :
(L - L0) / 2 * ‖ηhat - β‖ ^ 2 + F f lam q ηhat ≤ F f lam q β := by sorry
end SubsetShrink.DFO
Source
Mazumder, Radchenko & Dedieu, Subset Selection with Shrinkage, arXiv:1708.03288v4, p. 35, proof of Proposition 2 (A.1), (22)
Human review
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.