2017
Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation
AISTATS 2017poster
We propose a flexible convex relaxation for the phase retrieval problem that operates in the natural domain of the signal. Therefore, we avoid the prohibitive computational cost associated with “lifting” and semidefinite programming (SDP) in methods such as PhaseLift and compete with recently develo…