Hadamard wirtinger flow for sparse phase retrieval
We consider the problem of reconstructing an n-dimensional k-sparse signal from a set of noiseless magnitude-only measurements. Formulating the problem as an unregularized empirical risk minimization task, we study the sample complexity performance of gradient descent with Hadamard parametrization,...
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| Aineistotyyppi: | Conference item |
| Kieli: | English |
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Journal of Machine Learning Research
2021
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