Published in IEEE Trans. on Signal Processing (To appear), 2021
We formulate agnostic matrix phase retrieval as a rank-restricted largest eigenvalue problem by applying the second-order Stein’s identity, and propose a new spectrum truncation power iteration (STPower) method to obtain the desired matrix efficiently. Also, we show a favorable rank recovery result by adopting the STPower method, i.e., a near-optimal statistical convergence rate under relatively general model assumptions from a wide range of applications.
Recommended citation: Liu, L., Lu, S., Zhao, T. & Wang, Z. Spectrum Truncation Power Iteration for Matrix Phase Retrieval. IEEE Trans. on Signal Processing, 2021+. http://lewis-algo.com/files/TSP_matrix.pdf