Pages that link to "Item:Q2500458"

The following pages link to High-dimensional graphs and variable selection with the Lasso (Q2500458):

Displaying 50 items.

• A note on the Lasso for Gaussian graphical model selection (Q927362) (← links)
• Discussion: One-step sparse estimates in nonconcave penalized likelihood models (Q939651) (← links)
• Rejoinder: One-step sparse estimates in nonconcave penalized likelihood models (Q939653) (← links)
• The sparsity and bias of the LASSO selection in high-dimensional linear regression (Q939654) (← links)
• ``Preconditioning'' for feature selection and regression in high-dimensional problems (Q939656) (← links)
• Tests for Gaussian graphical models (Q961382) (← links)
• High-dimensional Ising model selection using \(\ell _{1}\)-regularized logistic regression (Q973867) (← links)
• Least angle and \(\ell _{1}\) penalized regression: a review (Q975564) (← links)
• Estimating time-varying networks (Q977626) (← links)
• High-dimensional Gaussian model selection on a Gaussian design (Q985331) (← links)
• Variable selection in nonparametric additive models (Q988006) (← links)
• SPADES and mixture models (Q988014) (← links)
• Estimation of covariance matrix via the sparse Cholesky factor with lasso (Q993832) (← links)
• Flexible covariance estimation in graphical Gaussian models (Q1000308) (← links)
• Lasso-type recovery of sparse representations for high-dimensional data (Q1002157) (← links)
• Relaxed Lasso (Q1020826) (← links)
• SCAD-penalized regression in high-dimensional partially linear models (Q1020975) (← links)
• High-dimensional additive modeling (Q1043712) (← links)
• Sparsistency and rates of convergence in large covariance matrix estimation (Q1043730) (← links)
• Estimating high-dimensional intervention effects from observational data (Q1043733) (← links)
• Robust methods for inferring sparse network structures (Q1615086) (← links)
• Edge detection in sparse Gaussian graphical models (Q1615220) (← links)
• Change-point detection in high-dimensional covariance structure (Q1616311) (← links)
• A general family of trimmed estimators for robust high-dimensional data analysis (Q1616324) (← links)
• Nonparametric Bayesian learning of heterogeneous dynamic transcription factor networks (Q1621019) (← links)
• Estimating a common covariance matrix for network meta-analysis of gene expression datasets in diffuse large B-cell lymphoma (Q1621047) (← links)
• A joint convex penalty for inverse covariance matrix estimation (Q1623469) (← links)
• Solving norm constrained portfolio optimization via coordinate-wise descent algorithms (Q1623568) (← links)
• The cluster graphical Lasso for improved estimation of Gaussian graphical models (Q1623817) (← links)
• Model selection consistency of Lasso for empirical data (Q1624086) (← links)
• Penalised inference for lagged dependent regression in the presence of autocorrelated residuals (Q1640650) (← links)
• Statistics for big data: a perspective (Q1642374) (← links)
• Distributed testing and estimation under sparse high dimensional models (Q1650081) (← links)
• Sparse linear models and \(l_1\)-regularized 2SLS with high-dimensional endogenous regressors and instruments (Q1652952) (← links)
• Recent developments in high dimensional covariance estimation and its related issues, a review (Q1657856) (← links)
• Bayesian variable selection with strong heredity constraints (Q1657864) (← links)
• High-dimensional inference for personalized treatment decision (Q1657878) (← links)
• High dimensional Gaussian copula graphical model with FDR control (Q1658182) (← links)
• On stepwise pattern recovery of the fused Lasso (Q1660156) (← links)
• On the sign consistency of the Lasso for the high-dimensional Cox model (Q1661333) (← links)
• Joint estimation of multiple Gaussian graphical models across unbalanced classes (Q1662174) (← links)
• Moderately clipped Lasso (Q1663146) (← links)
• Finding Dantzig selectors with a proximity operator based fixed-point algorithm (Q1663200) (← links)
• Probing for sparse and fast variable selection with model-based boosting (Q1664500) (← links)
• Confidence regions for entries of a large precision matrix (Q1668572) (← links)
• Generalized Kalman smoothing: modeling and algorithms (Q1678609) (← links)
• Sparse causality network retrieval from short time series (Q1687426) (← links)
• Sparse and low-rank matrix regularization for learning time-varying Markov networks (Q1689602) (← links)
• High-dimensional simultaneous inference with the bootstrap (Q1694480) (← links)
• A constrained \(\ell1\) minimization approach for estimating multiple sparse Gaussian or nonparanormal graphical models (Q1698844) (← links)