Universality in polytope phase transitions and message passing algorithms 论文

2015The Annals of Applied Probability引用 223
Sparse and Compressive Sensing TechniquesBlind Source Separation TechniquesTopological and Geometric Data Analysis

详细信息

发表期刊/会议
The Annals of Applied Probability
发表日期
2015-02-19
发表年份
2015

关键词

Sparse and Compressive Sensing TechniquesBlind Source Separation TechniquesTopological and Geometric Data Analysis

摘要

We consider a class of nonlinear mappings $\mathsf{F}_{A,N}$ in $\mathbb{R}^{N}$ indexed by symmetric random matrices $A\in\mathbb{R}^{N\times N}$ with independent entries. Within spin glass theory, special cases of these mappings correspond to iterating the TAP equations and were studied by Bolthausen [Comm. Math. Phys. 325 (2014) 333–366]. Within information theory, they are known as “approximate message passing” algorithms. We study the high-dimensional (large $N$) behavior of the iterates of $\mathsf{F}$ for polynomial functions $\mathsf{F}$, and prove that it is universal; that is, it depends only on the first two moments of the entries of $A$, under a sub-Gaussian tail condition. As an application, we prove the universality of a certain phase transition arising in polytope geometry and compressed sensing. This solves, for a broad class of random projections, a conjecture by David Donoho and Jared Tanner.

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