4 papers
Orthogonal Approximate Message Passing Algorithms for Rectangular Spiked Matrix Models with Rotationally Invariant Noise
Haohua Chen, Songbin Liu, Junjie Ma
We propose an orthogonal approximate message passing (OAMP) algorithm for signal estimation in the rectangular spiked matrix model with general rotationally invariant (RI) noise. W…
Orthogonal Approximate Message Passing with Optimal Spectral Initializations for Rectangular Spiked Matrix Models
Haohua Chen, Songbin Liu, Junjie Ma
We propose an orthogonal approximate message passing (OAMP) algorithm for signal estimation in the rectangular spiked matrix model with general rotationally invariant (RI) noise. W…
Optimality of Approximate Message Passing Algorithms for Spiked Matrix Models with Rotationally Invariant Noise
Rishabh Dudeja, Songbin Liu, Junjie Ma
We study the problem of estimating a rank one signal matrix from an observed matrix generated by corrupting the signal with additive rotationally invariant noise. We develop a new…
Unifying AMP Algorithms for Rotationally-Invariant Models
Songbin Liu, Junjie Ma
This paper presents a unified framework for constructing Approximate Message Passing (AMP) algorithms for rotationally-invariant models. By employing a general iterative algorithm…