Huber-loss phase retrieval with ℓ1/2 regularization is consistent in the real case, satisfies a fixed point inclusion in the complex case, and admits a provably convergent MM algorithm with a conditional linear rate.
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Robust Sparse Phase Retrieval: Statistical Guarantee, Optimality Theory and Convergent Algorithm
Huber-loss phase retrieval with ℓ1/2 regularization is consistent in the real case, satisfies a fixed point inclusion in the complex case, and admits a provably convergent MM algorithm with a conditional linear rate.