Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  study the problem of recovering a low-rank matrix, X, from phaseless measurements of random linear projections of its columns.  develop a novel solution approach, called AltMinTrunc, that consists of a two-step truncated spectral initialization step, follod by a three-step alternating minimization algorithm.  also obtain sample complexity bounds for the AltMinTrunc initialization to provide a good approximation of the true X. When the rank is low enough, these bounds are significantly smaller than what existing single vector phase retrieval algorithms need. Via extensive experiments,  show that the same is true for the entire algorithm.
['Namrata Vaswani', 'Seyedehsara Nayer', 'Yonina C. Eldar']
I am writing a research paper on a idea Low Rank Phase Retrieval
[{"from": "human", "value": "I am writing a research paper on a idea Low Rank Phase Retrieval"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  study the problem of recovering a low-rank matrix, X, from phaseless measurements of random linear projections of its columns.  develop a novel solution approach, called AltMinTrunc, that consists of a two-step truncated spectral initialization step, follod by a three-step alternating minimization algorithm.  also obtain sample complexity bounds for the AltMinTrunc initialization to provide a good approximation of the true X. When the rank is low enough, these bounds are significantly smaller than what existing single vector phase retrieval algorithms need. Via extensive experiments,  show that the same is true for the entire algorithm."}]