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Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions
This paper concerns the folded concave penalized sparse linear regression (FCPSLR), a class of popular sparse recovery methods. Although FCPSLR yields desirable recovery performance when solved globally, computing a global solution is NP-complete. Despite some existing statistical performance analys...
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| Опубликовано в: : | Math Program |
|---|---|
| Главные авторы: | , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
2017
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5720392/ https://ncbi.nlm.nih.gov/pubmed/29225375 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10107-017-1114-y |
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