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ledoux_talagrand_finite_bernoulli_coordinate_process_log_tail

Proved

by Shuze Chen · Jun 29, 2026 · Mathlib c5ea003 (Lean v4.30.0)

appendix-9-1bernoullicandes-rechtconcentrationempirical-processledouxtalagrandtextbook-result

This is the finite Bernoulli-coordinate specialization of the textbook Talagrand--Ledoux concentration theorem for bounded centered empirical-process suprema.

Let Ω⊆[n1]×[n2]\Omega\subseteq [n_1]\times[n_2]Ω⊆[n1​]×[n2​] be sampled in the independent Bernoulli model with

p=mn1n2.p=\frac{m}{n_1n_2}.p=n1​n2​m​.

For each element aaa of a finite nonempty index class, let ca(i,j)c_a(i,j)ca​(i,j) be a real coefficient array and define the centered coordinate sum

Sa(Ω)=∑i,j(1(i,j)∈Ω−p)ca(i,j).S_a(\Omega)=\sum_{i,j}\bigl(1_{(i,j)\in\Omega}-p\bigr)c_a(i,j).Sa​(Ω)=i,j∑​(1(i,j)∈Ω​−p)ca​(i,j).

Set

Z(Ω)=max⁡aSa(Ω),Zˉ(Ω)=max⁡a∣Sa(Ω)∣.Z(\Omega)=\max_a S_a(\Omega),\qquad \bar Z(\Omega)=\max_a |S_a(\Omega)|.Z(Ω)=amax​Sa​(Ω),Zˉ(Ω)=amax​∣Sa​(Ω)∣.

Assume the uniform envelope bound

∣ca(i,j)∣≤Bfor all a,i,j,|c_a(i,j)|\le B\quad\text{for all }a,i,j,∣ca​(i,j)∣≤Bfor all a,i,j,

with B>0B>0B>0, and the Bernoulli variance proxy bound

∑i,jp(1−p)ca(i,j)2≤σ2for every a.\sum_{i,j}p(1-p)c_a(i,j)^2\le \sigma^2 \quad\text{for every }a.i,j∑​p(1−p)ca​(i,j)2≤σ2for every a.

Then there is a universal numerical constant K>0K>0K>0 such that for every t≥0t\ge0t≥0,

Pp(∣Z−EpZ∣≤t)≥1−3exp⁡(−tKBlog⁡(1+Btσ2+BEpZˉ)).\mathbb P_p\left(|Z-\mathbb E_p Z|\le t\right) \ge 1-3\exp\left( -{t\over KB}\log\left(1+{Bt\over \sigma^2+B\mathbb E_p\bar Z}\right) \right).Pp​(∣Z−Ep​Z∣≤t)≥1−3exp(−KBt​log(1+σ2+BEp​ZˉBt​)).

This node is intended as the textbook terminal analytic input for the Candès--Recht Appendix 9.1 Talagrand step. The absolute supremum Zˉ\bar ZZˉ is kept because this is the standard non-symmetric empirical-process form; the symmetric Candès--Recht specialization is obtained by the elementary identity Zˉ=Z\bar Z=ZZˉ=Z when the coefficient class is closed under c↦−cc\mapsto -cc↦−c.

Source location: Ledoux, The Concentration of Measure Phenomenon, Section 7, Corollary 7.8. The equivalent local lecture-note statement is Ledoux, Section 3.4, Theorem 3.6 plus the following paragraph stating that the same bound controls P{∣Z−EZ∣≥r}\mathbb P\{|Z-\mathbb E Z|\ge r\}P{∣Z−EZ∣≥r} up to numerical constants. Candès--Romberg, PDF p. 11, Theorem 3.2, cites this Ledoux corollary before applying it to Bernoulli coordinate sampling; Candès--Recht Appendix 9.1, PDF p. 46, invokes the symmetric form as Theorem 9.1.

Preamble
import Definitions.Def_matrix_completion_bernoulli
import Mathlib.Analysis.SpecialFunctions.Log.Basic

open MatrixCompletion
open scoped Classical BigOperators
Formal statement
theorem ledoux_talagrand_finite_bernoulli_coordinate_process_log_tail :
    ∃ K : ℝ, 0 < K ∧
      ∀ (n₁ n₂ m : ℕ) (ι : Type) [Fintype ι] [Nonempty ι]
        (coeff : ι → Fin n₁ → Fin n₂ → ℝ) (B sigmaSq t : ℝ),
        0 < n₁ → 0 < n₂ → m ≤ n₁ * n₂ →
        0 < B → 0 ≤ sigmaSq → 0 ≤ t →
        (∀ a : ι, ∀ i : Fin n₁, ∀ j : Fin n₂,
          |coeff a i j| ≤ B) →
        (∀ a : ι,
          ∑ i : Fin n₁, ∑ j : Fin n₂,
            ((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ))) *
              (1 - ((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ)))) *
                (coeff a i j) ^ 2 ≤ sigmaSq) →
        let p : ℝ := (m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ))
        let process : ι → Finset (Fin n₁ × Fin n₂) → ℝ :=
          fun a Omega =>
            ∑ i : Fin n₁, ∑ j : Fin n₂,
              (((if (i, j) ∈ Omega then (1 : ℝ) else 0) - p) *
                coeff a i j)
        let Z : Finset (Fin n₁ × Fin n₂) → ℝ :=
          fun Omega =>
            Finset.univ.sup' Finset.univ_nonempty (fun a : ι => process a Omega)
        let Zbar : Finset (Fin n₁ × Fin n₂) → ℝ :=
          fun Omega =>
            Finset.univ.sup' Finset.univ_nonempty
              (fun a : ι => |process a Omega|)
        bernoulliEventProb p
            (fun Omega => |Z Omega - bernoulliExpectation p Z| ≤ t) ≥
          1 -
            3 * Real.exp
              (-(t / (K * B)) *
                Real.log
                  (1 + (B * t) /
                    (sigmaSq + B * bernoulliExpectation p Zbar))) := by
  sorry
Source
Ledoux, Michel. The Concentration of Measure Phenomenon. American Mathematical Society, 2001, Section 7, Corollary 7.8; finite Bernoulli-coordinate specialization used in Candes-Recht Appendix 9.1.

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