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The Sparse MLE for Ultra-High-Dimensional Feature Screening

Feature selection is fundamental for modeling the high dimensional data, where the number of features can be huge and much larger than the sample size. Since the feature space is so large, many traditional procedures become numerically infeasible. It is hence essential to first remove most apparentl...

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Bibliografiska uppgifter
I publikationen:J Am Stat Assoc
Huvudupphovsmän: Xu, Chen, Chen, Jiahua
Materialtyp: Artigo
Språk:Inglês
Publicerad: 2014
Ämnen:
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC4219371/
https://ncbi.nlm.nih.gov/pubmed/25382886
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2013.879531
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