quadratic_neumann_all_distinct_inner_coefficients_from_base_bounds_min_dim_shifted
OpenFormal bridge from the corrected min-dimension pointwise all-distinct inner coefficient tail to the simultaneous coefficient event with the required ordered-pair union-bound shift.
Primary reference: Candes--Recht, Exact Matrix Completion via Convex Optimization, PDF p. 28, Section 6.2, Lemma 6.6, equations (6.15)--(6.17), the union-bound discussion after equation (6.17), and PDF p. 30, Section 6.3, equation (6.20).
Mathematical statement and notation: set and . The event is over the Bernoulli sample with probability bernoulliEventProb p. For SVD data satisfying and , equation (6.20) identifies each all-distinct inner coefficient as
Assume the corrected min-dimension entry and Frobenius bounds for and the sample lower bound both at exponent and at shifted exponent :
Then, after applying the pointwise child at exponent and paying the ordered-pair union-bound cost , the simultaneous event holds:
Here , the Bernoulli model, and the coefficient family are named explicitly. and fixed-cardinality successProb do not appear in this local coefficient bridge.
Formalization note: this is a formal bridge, not a theorem appearing verbatim in the paper. It should import the source-backed pointwise child quadratic_neumann_all_distinct_inner_coefficient_pointwise_tail_from_base_bounds_min_dim and the already proved source-backed uniformization child quadratic_neumann_all_distinct_inner_coefficients_uniform_from_shifted_pointwise_tails (c325fcc3-f5e1-48f4-acdb-12c7ae7ea619). The bridge replaces the stale old route through quadratic_neumann_all_distinct_inner_coefficients_from_base_bounds, whose accepted sketch uses the deprecated unshifted uniformization child.
import Definitions.Def_matrix_completion_neumann open MatrixCompletion
theorem quadratic_neumann_all_distinct_inner_coefficients_from_base_bounds_min_dim_shifted
(Centry Cfro : ℝ) :
0 < Centry → 0 < Cfro →
∃ Cinner cinner : ℝ, 0 < Cinner ∧ 0 < cinner ∧
∀ (β lam : ℝ), 2 < β → 1 ≤ lam →
∀ (n₁ n₂ r m : ℕ) (M : Matrix (Fin n₁) (Fin n₂) ℝ)
(μ₀ μ₁ : ℝ) (S : SVD M r),
0 < n₁ → 0 < n₂ → 0 < r → m ≤ n₁ * n₂ →
1 ≤ μ₀ → 1 ≤ μ₁ →
A0 S μ₀ → A1 S μ₁ →
(m : ℝ) ≥
lam * Real.rpow μ₀ ((4 : ℝ) / 3) *
(↑(max n₁ n₂)) * Real.rpow (r : ℝ) ((4 : ℝ) / 3) *
(β * Real.log (↑(max n₁ n₂))) →
(m : ℝ) ≥
lam * Real.rpow μ₀ ((4 : ℝ) / 3) *
(↑(max n₁ n₂)) * Real.rpow (r : ℝ) ((4 : ℝ) / 3) *
((β + 4) * Real.log (↑(max n₁ n₂))) →
(∀ (Omega3 : Finset (Fin n₁ × Fin n₂))
(w1 w2 : Fin n₁ × Fin n₂),
quadraticAllDistinctInnerCoefficient Omega3 S
((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ))) w1 w2 =
matrixEntrySum
(centeredSamplingFluctuation Omega3
((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ)))
(quadraticAllDistinctInnerBaseMatrix S w1 w2))) →
(∀ w1 w2 : Fin n₁ × Fin n₂,
entrySupNorm (quadraticAllDistinctInnerBaseMatrix S w1 w2) ≤
Centry * μ₁ *
Real.sqrt ((r : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ))) *
(μ₀ * (r : ℝ) / (↑(min n₁ n₂)))) →
(∀ w1 w2 : Fin n₁ × Fin n₂,
frobeniusNorm (quadraticAllDistinctInnerBaseMatrix S w1 w2) ≤
Cfro * μ₁ *
Real.sqrt ((r : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ))) *
Real.sqrt (μ₀ * (r : ℝ) / (↑(min n₁ n₂)))) →
bernoulliEventProb ((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ)))
(fun Omega3 =>
QuadraticAllDistinctInnerCoefficientBound Omega3 S
((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ)))
(Cinner * Real.rpow lam (-((1 : ℝ) / 2)))) ≥
1 - cinner * Real.rpow (↑(max n₁ n₂)) (-β) := by
sorry