scientific article; zbMATH DE number 7370571
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Publication:4998947
Xinming Yang, Feng Liang, Lingrui Gan, Naveen Naidu Narisetty
Publication date: 9 July 2021
Full work available at URL: https://jmlr.csail.mit.edu/papers/v22/19-1006.html
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
EM algorithmnon-convex optimizationgraphical modelsselection consistencyBayesian regularizationspike-and-slab priors
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Cites Work
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- Penalized methods for bi-level variable selection
- Sparse inverse covariance estimation with the graphical lasso
- Bayesian structure learning in sparse Gaussian graphical models
- Bayesian variable selection and estimation for group Lasso
- Support recovery without incoherence: a case for nonconvex regularization
- Gibbs posterior for variable selection in high-dimensional classification and data mining
- Sparsistency and rates of convergence in large covariance matrix estimation
- Bayesian inference for multiple Gaussian graphical models with application to metabolic association networks
- Bayesian estimation of sparse signals with a continuous spike-and-slab prior
- Efficient Gaussian graphical model determination under \(G\)-Wishart prior distributions
- The graphical lasso: new insights and alternatives
- Sparse permutation invariant covariance estimation
- High-dimensional covariance estimation by minimizing \(\ell _{1}\)-penalized log-determinant divergence
- Bayesian structure learning in graphical models
- Network exploration via the adaptive LASSO and SCAD penalties
- A Constrainedℓ1Minimization Approach to Sparse Precision Matrix Estimation
- Emergence of Scaling in Random Networks
- Joint estimation of multiple graphical models
- Bayesian Inference for General Gaussian Graphical Models With Application to Multivariate Lattice Data
- Objective Bayesian model selection in Gaussian graphical models
- Model selection and estimation in the Gaussian graphical model
- A group bridge approach for variable selection
- The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes
- Bayesian Regularization for Graphical Models With Unequal Shrinkage
- Fused Multiple Graphical Lasso
- Bayesian Inference of Multiple Gaussian Graphical Models
- The average distances in random graphs with given expected degrees
- Strong Rules for Discarding Predictors in Lasso-Type Problems
- A selective review of group selection in high-dimensional models
