Name
Abstract | ||
|---|---|---|
Generalized cross validation is a popular approach to determining the regularization parameter in Tikhonov regularization. The regularization parameter is chosen by minimizing an expression, which is easy to evaluate for small-scale problems, but prohibitively expensive to compute for large-scale ones. This paper describes a novel method, based on Gauss-type quadrature, for determining upper and lower bounds for the desired expression. These bounds are used to determine the regularization parameter for large-scale problems. Computed examples illustrate the performance of the proposed method and demonstrate its competitiveness. Copyright (C) 2016 John Wiley & Sons, Ltd. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1002/nla.2034 | NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS |
Keywords | Field | DocType |
generalized cross validation,Tikhonov regularization,parameter estimation,global Golub-Kahan decomposition | Tikhonov regularization,Mathematical optimization,Regularization (mathematics),Estimation theory,Mathematics | Journal |
Volume | Issue | ISSN |
23.0 | 3.0 | 1070-5325 |
Citations | PageRank | References |
4 | 0.48 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Caterina Fenu | 1 | 20 | 3.64 |
| Lothar Reichel | 2 | 453 | 95.02 |
| Giuseppe Rodriguez | 3 | 197 | 29.43 |