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The lasso model has been widely used for model selection in data mining, machine learning, and high-dimensional statistical analysis.
Regression shrinkage and selection via the lasso
Tibshirani, R · 1996
Earlier work this paper cites.
Convex optimization
Boyd, S · 2004
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Least angle regression
Efron, B · 2004
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Regularization and variable selection via the elastic net
Zou, H · 2005
Earlier work this paper cites.
Model selection and estimation in regression with grouped variables
Yuan, M · 2006
Earlier work this paper cites.
Pathwise coordinate optimization
Friedman, J · 2007
Earlier work this paper cites.
An interior-point method for large-scale-regularized least squares
Kim, S.-J · 2007
Earlier work this paper cites.
Efficient sparse coding algorithms
Lee, H · 2007
Earlier work this paper cites.
Sure independence screening for ultrahigh dimensional feature space
Fan, J · 2008
Earlier work this paper cites.
The group lasso for logistic regression
Meier, L · 2008
Earlier work this paper cites.
Coordinate descent algorithms for lasso penalized regression
Wu, T. T · 2008
Earlier work this paper cites.
Rls-weighted lasso for adaptive estimation of sparse signals
Angelosante, D · 2009
Cited alongside, same era.
An homotopy algorithm for the lasso with online observations
Garrigues, P · 2009
Cited alongside, same era.
Robust face recognition via sparse representation
Wright, J · 2009
Cited alongside, same era.
A map of human genome variation from population-scale sequencing
Consortium, . G. P · 2010
Cited alongside, same era.
Regularization paths for generalized linear models via coordinate descent
Friedman, J · 2010
Cited alongside, same era.
Safe feature elimination for the lasso and sparse supervised learning problems
Ghaoui, L. E · 2010
Cited alongside, same era.
Fast lasso screening tests based on correlations
Xiang, Z. J · 2012
Later among the works it cites.
UCI machine learning repository
Lichman, M · 2013
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Efficient block-coordinate descent algorithms for the group lasso
Qin, Z · 2013
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Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors
Breheny, P · 2015
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Strong rules for nonconvex penalties and their implications for efficient algorithms in high-dimensional regression
Lee, S · 2015
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Relevance feature discovery for text mining
Li, Y · 2015
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Genetic analysis workshop 17 mini-exome simulation
Almasy, L · 2011
Cited alongside, same era.
Distributed optimization and statistical learning via the alternating direction method of multipliers
Boyd, S · 2011
Cited alongside, same era.
Stochastic methods for l1-regularized loss minimization
Shalev-Shwartz, S · 2011
Cited alongside, same era.
Learning sparse representations of high dimensional data on large scale dictionaries
Xiang, Z. J · 2011
Cited alongside, same era.
Strong rules for discarding predictors in lasso-type problems
Tibshirani, R · 2012
Cited alongside, same era.
Lasso screening rules via dual polytope projection
Wang, J · 2015
Later among the works it cites.
Screening tests for lasso problems
Xiang, Z. J · 2016
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The biglasso package: A memory- and computation-efficient solver for lasso model fitting with big data in r
Zeng, Y · 2017
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Linear regression and two-class classification with gene expression data
Huang, X · 2078
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