Name
Abstract | ||
|---|---|---|
In this paper, the task of robust estimation in the presence of outliers is presented. Outliers are explicitly modeled by employing sparsity arguments. A novel efficient algorithm, based on the greedy Orthogonal Matching Pursuit (OMP) scheme, is derived. Theoretical results concerning the recovery of the solution as well as simulation experiments, which verify the comparative advantages of the new technique, are discussed. |
Year | Venue | Keywords |
|---|---|---|
2014 | Signal Processing Conference | estimation theory,iterative methods,regression analysis,signal processing,time-frequency analysis,OMP scheme,greedy orthogonal matching pursuit scheme,greedy way,outlier presence,robust estimation,robust linear regression analysis,sparsity arguments,Greedy Algorithm for Robust Denoising (GARD),Greedy algorithms,Outlier detection,Robust Least Squares,Robust based Regression |
Field | DocType | ISSN |
Matching pursuit,Mathematical optimization,Outlier,Greedy algorithm,Robust regression,Greedy randomized adaptive search procedure,Mathematics | Conference | 2076-1465 |
Citations | PageRank | References |
3 | 0.39 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| George Papageorgiou | 1 | 10 | 3.21 |
| Pantelis Bouboulis | 2 | 171 | 11.05 |
| Sergios Theodoridis | 3 | 1353 | 106.97 |
| Konstantinos Themelis | 4 | 3 | 0.39 |