Name
Abstract | ||
|---|---|---|
The problem of low-rank matrix completion is considered in this paper. To exploit the underlying low-rank structure of the data matrix, we propose a hierarchical Gaussian prior model, where columns of the low-rank matrix are assumed to follow a Gaussian distribution with zero mean and a common precision matrix, and a Wishart distribution is specified as a hyperprior over the precision matrix. We s... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TSP.2018.2816575 | IEEE Transactions on Signal Processing |
Keywords | DocType | Volume |
Bayes methods,Gaussian distribution,Covariance matrices,Computational modeling,Electronic mail,Sparse matrices,Data models | Journal | 66 |
Issue | ISSN | Citations |
11 | 1053-587X | 3 |
PageRank | References | Authors |
0.38 | 12 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Linxiao Yang | 1 | 77 | 6.45 |
| Jun Fang | 2 | 1039 | 94.15 |
| Huiping Duan | 3 | 137 | 13.43 |
| Hongbin Li | 4 | 137 | 11.40 |
| B Zeng | 5 | 1374 | 159.35 |