centered_sampling_jensen_pointwise_independent_copy_bound_of_sample_ratio
Provedbernoulli-samplingcandes-rechtjensen-inequalitylean4matrix-completionsection-6-1symmetrization
This is the pointwise Jensen step in the independent-copy symmetrization argument of Candes-Recht Section 6.1.
Let
Assume , , and , so is a genuine Bernoulli sampling probability. For every fixed observation set , every matrix , and every integer , Jensen's inequality applied to an independent copy gives
The reason is that the centered sampling fluctuation has mean zero, so
and the function is convex for .
Source: Candes-Recht 2008, PDF p. 24, Section 6.1, equation (6.5) and the paragraph applying Jensen's inequality to .
Preamble
import Definitions.Def_matrix_completion_rademacher open MatrixCompletion
Formal statement
theorem centered_sampling_jensen_pointwise_independent_copy_bound_of_sample_ratio :
∀ (n₁ n₂ m q : ℕ) (X : Matrix (Fin n₁) (Fin n₂) ℝ),
0 < n₁ → 0 < n₂ → m ≤ n₁ * n₂ → 1 ≤ q →
∀ Omega : Finset (Fin n₁ × Fin n₂),
spectralNorm
(centeredSamplingFluctuation Omega
((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ))) X) ^ q ≤
bernoulliExpectation ((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ)))
(fun Omega' =>
spectralNorm
(centeredSamplingFluctuation Omega
((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ))) X -
centeredSamplingFluctuation Omega'
((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ))) X) ^ q) := by
sorry
Source
Candes, Emmanuel, and Benjamin Recht. "Exact matrix completion via convex optimization." Communications of the ACM 55.6 (2012): 111-119.