Phase Retrieval using Alternating Minimization

Neural Information Processing Systems 

Phase retrieval problems involve solving linear equations, but with missing sign (or phase, for complex numbers). Over the last two decades, a popular generic empirical approach to the many variants of this problem has been one of alternating minimization; i.e. alternating between estimating the missing phase information, and the candidate solution.