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An imputation–regularized optimization algorithm for high dimensional missing data problems and beyond

Missing data are frequently encountered in high dimensional problems, but they are usually difficult to deal with by using standard algorithms, such as the expectation-maximization algorithm and its variants. To tackle this difficulty, some problem-specific algorithms have been developed in the lite...

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Bibliographic Details
Published in:J R Stat Soc Series B Stat Methodol
Main Authors: Liang, Faming, Jia, Bochao, Xue, Jingnan, Li, Qizhai, Luo, Ye
Format: Artigo
Language:Inglês
Published: 2018
Subjects:
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC6533005/
https://ncbi.nlm.nih.gov/pubmed/31130816
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/rssb.12279
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