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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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| I publikationen: | PLoS One |
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| Huvudupphovsmän: | , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
Public Library of Science
2015
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| Ämnen: | |
| Länkar: | 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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