Pages that link to "Item:Q2388978"

The following pages link to Simultaneous analysis of Lasso and Dantzig selector (Q2388978):

Displaying 50 items.

• A simple forward selection procedure based on false discovery rate control (Q1018611) (← links)
• Sparse recovery in convex hulls via entropy penalization (Q1018643) (← links)
• High-dimensional additive modeling (Q1043712) (← links)
• Nonnegative-Lasso and application in index tracking (Q1615217) (← links)
• Significance testing in non-sparse high-dimensional linear models (Q1616315) (← links)
• On the prediction loss of the Lasso in the partially labeled setting (Q1616320) (← links)
• A linear programming model for selection of sparse high-dimensional multiperiod portfolios (Q1622825) (← links)
• Model selection consistency of Lasso for empirical data (Q1624086) (← links)
• Signal recovery under cumulative coherence (Q1624658) (← links)
• High-dimensional \(A\)-learning for optimal dynamic treatment regimes (Q1650064) (← links)
• Are discoveries spurious? Distributions of maximum spurious correlations and their applications (Q1650067) (← links)
• Variational multiscale nonparametric regression: smooth functions (Q1650131) (← links)
• Sparse linear models and \(l_1\)-regularized 2SLS with high-dimensional endogenous regressors and instruments (Q1652952) (← links)
• High dimensional Gaussian copula graphical model with FDR control (Q1658182) (← links)
• Trace regression model with simultaneously low rank and row(column) sparse parameter (Q1658399) (← links)
• Structured variable selection via prior-induced hierarchical penalty functions (Q1659467) (← links)
• Variable selection for high dimensional Gaussian copula regression model: an adaptive hypothesis testing procedure (Q1662864) (← links)
• Balanced estimation for high-dimensional measurement error models (Q1663093) (← links)
• Relaxed sparse eigenvalue conditions for sparse estimation via non-convex regularized regression (Q1677029) (← links)
• A doubly sparse approach for group variable selection (Q1680797) (← links)
• Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions (Q1683689) (← links)
• Estimator selection: a new method with applications to kernel density estimation (Q1688428) (← links)
• A Rice method proof of the null-space property over the Grassmannian (Q1700392) (← links)
• Estimating a sparse reduction for general regression in high dimensions (Q1702278) (← links)
• Inferring large graphs using \(\ell_1\)-penalized likelihood (Q1704026) (← links)
• A group adaptive elastic-net approach for variable selection in high-dimensional linear regression (Q1705570) (← links)
• Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative Lasso (Q1706454) (← links)
• Linear regression with sparsely permuted data (Q1711600) (← links)
• An analysis of the SPARSEVA estimate for the finite sample data case (Q1716452) (← links)
• A two-stage regularization method for variable selection and forecasting in high-order interaction model (Q1723055) (← links)
• A systematic review on model selection in high-dimensional regression (Q1726155) (← links)
• Nonconvex penalized ridge estimations for partially linear additive models in ultrahigh dimension (Q1731372) (← links)
• Signal recovery under mutual incoherence property and oracle inequalities (Q1731904) (← links)
• Determination of vector error correction models in high dimensions (Q1739869) (← links)
• Oracle inequalities for high-dimensional prediction (Q1740524) (← links)
• Variable screening for high dimensional time series (Q1746535) (← links)
• Improved bounds for square-root Lasso and square-root slope (Q1746538) (← links)
• A strong converse bound for multiple hypothesis testing, with applications to high-dimensional estimation (Q1746556) (← links)
• Pathwise coordinate optimization for sparse learning: algorithm and theory (Q1747736) (← links)
• High dimensional censored quantile regression (Q1747740) (← links)
• Bayesian estimation of sparse signals with a continuous spike-and-slab prior (Q1747745) (← links)
• Column normalization of a random measurement matrix (Q1748563) (← links)
• Regularization and the small-ball method. I: Sparse recovery (Q1750281) (← links)
• Oracle inequalities for sparse additive quantile regression in reproducing kernel Hilbert space (Q1750287) (← links)
• I-LAMM for sparse learning: simultaneous control of algorithmic complexity and statistical error (Q1750288) (← links)
• Sparse inference of the drift of a high-dimensional Ornstein-Uhlenbeck process (Q1755107) (← links)
• Optimal estimation of slope vector in high-dimensional linear transformation models (Q1755121) (← links)
• Time-varying Lasso (Q1787675) (← links)
• On the sensitivity of the Lasso to the number of predictor variables (Q1790389) (← links)
• Sliding-MOMP based channel estimation scheme for ISDB-T systems (Q1793180) (← links)