Name
Abstract | ||
|---|---|---|
This paper investigates the phase retrieval problem, which aims to recover a signal from the magnitudes of its linear measurements. We develop statistically and computationally efficient algorithms for the situation when the measurements are corrupted by sparse outliers that can take arbitrary values. We propose a novel approach to robustify the gradient descent algorithm by using the sample media... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TIT.2018.2847695 | IEEE Transactions on Information Theory |
Keywords | Field | DocType |
Extraterrestrial measurements,Robustness,Phase measurement,Loss measurement,Machine learning,Imaging,Optimization | Mathematical optimization,Gradient descent,Phase retrieval,Outlier,Gaussian,Artificial intelligence,Local search (optimization),Initialization,Logarithm,Spurious relationship,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
64 | 11 | 0018-9448 |
Citations | PageRank | References |
3 | 0.39 | 35 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huishuai Zhang | 1 | 34 | 12.56 |
| Yuejie Chi | 2 | 720 | 56.67 |
| Yingbin Liang | 3 | 1646 | 147.64 |