On the Use of Minimum Penalties in Statistical Learning

Cites Work

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Exact post-selection inference, with application to the Lasso
Correlated variables in regression: clustering and sparse estimation
Simultaneous multiple response regression and inverse covariance matrix estimation via penalized Gaussian maximum likelihood
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The smooth-Lasso and other \(\ell _{1}+\ell _{2}\)-penalized methods
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Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection
Likelihood-Based Selection and Sharp Parameter Estimation
Estimating Multiple Precision Matrices With Cluster Fusion Regularization
Regularization and Variable Selection Via the Elastic Net
Simultaneous Grouping Pursuit and Feature Selection Over an Undirected Graph
SPReM: Sparse Projection Regression Model For High-Dimensional Linear Regression
Foundations for Envelope Models and Methods
A significance test for graph‐constrained estimation
Estimating Linear Restrictions on Regression Coefficients for Multivariate Normal Distributions
A unified framework for high-dimensional analysis of \(M\)-estimators with decomposable regularizers

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