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,...
| Main Authors: | , |
|---|---|
| Format: | Conference item |
| Jezik: | English |
| Izdano: |
Journal of Machine Learning Research
2021
|