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We consider a popular nonsmooth formulation of the real phase retrieval problem.
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Gradient-based learning applied to document recognition
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Variational Analysis
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Variational Analysis and Generalized Differentiation I: Basic Theory
B.S. Mordukhovich · 2006
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Phaselift: Exact and stable signal recovery from magnitude measurements via convex programming
E.J. Candès, T. Strohmer, and V. Voroninski · 2013
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Matrix analysis
R.A. Horn and C.R. Johnson · 2013
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Phase retrieval: stability and recovery guarantees
Error bounds, quadratic growth, and linear convergence of proximal methods
D. Drusvyatskiy and A.S. Lewis · 2016
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Efficiency of minimizing compositions of convex functions and smooth maps
D. Drusvyatskiy and C. Paquette · 2016
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Solving systems of random quadratic equations via a truncated amplitude flow
G. Wang, G.B. Giannakis, and Y.C. Eldar · 2016
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Provable non-convex phase retrieval with outliers: Median truncated wirtinger flow
H. Zhang, Y. Chi, and Y. Liang · 2016
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Proximally guided stochastic method for nonsmooth, nonconvex problems
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Phase retrieval from very few measurements
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Phase retrieval via Wirtinger flow: theory and algorithms
E.J. Candès, X. Li, and M. Soltanolkotabi · 2015
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A proximal method for composite minimization
A.S. Lewis and S.J. Wright · 2015
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Solving (most) of a set of quadratic equalities: Composite optimization for robust phase retrieval
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