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The Marchenko–Pastur (MP) distribution describes the limiting eigenvalue distribution of sample covariance matrices S = (1/n) XX^{\top} when both the dimension p and the sample size n grow with p/n \to \gamma.
A proximal operator pulls a point x toward minimizing a function f while penalizing how far it moves, acting like a denoiser or projector depending on f.