Cargando…
Accelerating cross-validation with total variation and its application to super-resolution imaging
We develop an approximation formula for the cross-validation error (CVE) of a sparse linear regression penalized by ℓ(1)-norm and total variation terms, which is based on a perturbative expansion utilizing the largeness of both the data dimensionality and the model. The developed formula allows us t...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5720762/ https://www.ncbi.nlm.nih.gov/pubmed/29216215 http://dx.doi.org/10.1371/journal.pone.0188012 |