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Cross-validation (CV) methods are popular for selecting the tuning parameter in the high-dimensional variable selection problem.
An asymptotic equivalence of choice of model by cross-validation and akaike’s criterion
Stone, M · 1977
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Estimating the error rate of a prediction rule: Improvement on cross-validation
Efron, B · 1983
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How biased is the apparent error rate of a prediction rule?
Efron, B · 1986
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Linear model selection by cross-validation
Shao, J · 1993
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Basis pursuit
Chen, S · 1994
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Ideal spatial adaptation by wavelet shrinkage
Donoho, D. L · 1994
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Bootstrap model selection
Shao, J · 1996
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Regression shrinkage and selection via the lasso
Tibshirani, R · 1996
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Molecular classification of cancer: class discovery and class prediction by gene expression monitoring
Golub, T. R · 1999
Earlier work this paper cites.
Variable selection via nonconcave penalized likelihood and its oracle properties
Fan, J · 2001
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Exploration, normalization, and summaries of high density oligonucleotide array probe level data
Irizarry, R. A · 2003
Earlier work this paper cites.
Least angle regression
Efron, B · 2004
Cited alongside, same era.
Homozygosity mapping with snp arrays identifies trim32, an e3 ubiquitin ligase, as a bardet–biedl syndrome gene (bbs11)
Chiang, A. P · 2006
Cited alongside, same era.
Regulation of gene expression in the mammalian eye and its relevance to eye disease
Scheetz, T. E · 2006
Cited alongside, same era.
Relaxed lasso
Meinshausen, N · 2007
Cited alongside, same era.
An l 1 l_{1} regularization-path algorithm for generalized linear models
Park, M. Y · 2007
Cited alongside, same era.
Tuning parameter selectors for the smoothly clipped absolute deviation method
Wang, H · 2007
Cited alongside, same era.
Variable selection in nonparametric additive models
Huang, J · 2010
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l1-penalization for mixture regression models
Städler, N · 2010
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Nearly unbiased variable selection under minimax concave penalty
Zhang, C.-H · 2010
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Regularization parameter selections via generalized information criterion
Zhang, Y · 2010
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Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection
Breheny, P · 2011
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Statistics for High-Dimensional Data
Bühlmann, P · 2011
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Extended bayesian information criteria for model selection with large model spaces
Chen, J · 2008
Cited alongside, same era.
The sparsity and bias of the lasso selection in high-dimensional linear regression
Zhang, C.-H · 2008
Cited alongside, same era.
Shrinkage tuning parameter selection with a diverging number of parameters
Wang, H · 2009
Cited alongside, same era.
A selective overview of variable selection in high dimensional feature space
Fan, J · 2010
Cited alongside, same era.
Regularization paths for generalized linear models via coordinate descent
Friedman, J · 2010
Cited alongside, same era.
Apple: Approximate path for penalized likelihood estimators
Yu, Y
Cited in the paper.
Nonparametric independence screening in sparse ultra-high-dimensional additive models
Fan, J · 2011
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Scaled sparse linear regression
Sun, T · 2012
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Tuning parameter selection in high-dimensional penalized likelihood
Fan, Y · 2013
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Sequential lasso cum ebic for feature selection with ultra-high dimensional feature space
Luo, S · 2014
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