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Robust Generalized Low Rank Approximations of Matrices

In recent years, the intrinsic low rank structure of some datasets has been extensively exploited to reduce dimensionality, remove noise and complete the missing entries. As a well-known technique for dimensionality reduction and data compression, Generalized Low Rank Approximations of Matrices (GLR...

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Pubblicato in:PLoS One
Autori principali: Shi, Jiarong, Yang, Wei, Zheng, Xiuyun
Natura: Artigo
Lingua:Inglês
Pubblicazione: Public Library of Science 2015
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Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC4569376/
https://ncbi.nlm.nih.gov/pubmed/26367116
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0138028
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