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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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Bibliografski detalji
Izdano u:Adv Neural Inf Process Syst
Glavni autori: Wang, Zhaoran, Lu, Huanran, Liu, Han
Format: Artigo
Jezik:Inglês
Izdano: 2014
Teme:
Online pristup:https://ncbi.nlm.nih.gov/pmc/articles/PMC4301447/
https://ncbi.nlm.nih.gov/pubmed/25620858
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