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Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time
We provide statistical and computational analysis of sparse Principal Component Analysis (PCA) in high dimensions. The sparse PCA problem is highly nonconvex in nature. Consequently, though its global solution attains the optimal statistical rate of convergence, such solution is computationally intr...
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| Pubblicato in: | Adv Neural Inf Process Syst |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2014
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4301447/ https://ncbi.nlm.nih.gov/pubmed/25620858 |
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