Pages that link to "Item:Q147375"

The following pages link to The Adaptive Lasso and Its Oracle Properties (Q147375):

Displaying 50 items.

• Sparse regression with exact clustering (Q1952092) (← links)
• Majorization-minimization algorithms for nonsmoothly penalized objective functions (Q1952099) (← links)
• PAC-Bayesian bounds for sparse regression estimation with exponential weights (Q1952177) (← links)
• Automatic grouping using smooth-threshold estimating equations (Q1952187) (← links)
• The adaptive and the thresholded Lasso for potentially misspecified models (and a lower bound for the Lasso) (Q1952206) (← links)
• Robust regression through the Huber's criterion and adaptive lasso penalty (Q1952217) (← links)
• The smooth-Lasso and other \(\ell _{1}+\ell _{2}\)-penalized methods (Q1952223) (← links)
• Distributional results for thresholding estimators in high-dimensional Gaussian regression models (Q1952253) (← links)
• Sign-constrained least squares estimation for high-dimensional regression (Q1954143) (← links)
• Bridge estimation for generalized linear models with a diverging number of parameters (Q1957148) (← links)
• A cubic spline penalty for sparse approximation under tight frame balanced model (Q1986544) (← links)
• Variable selection for varying coefficient models via kernel based regularized rank regression (Q1987596) (← links)
• Pairwise fusion approach incorporating prior constraint information (Q1988277) (← links)
• Model-free feature screening for high-dimensional survival data (Q1989891) (← links)
• Slope meets Lasso: improved oracle bounds and optimality (Q1990596) (← links)
• High-dimensional consistency in score-based and hybrid structure learning (Q1991699) (← links)
• Advanced algorithms for penalized quantile and composite quantile regression (Q1995843) (← links)
• Penalized weighted composite quantile regression for partially linear varying coefficient models with missing covariates (Q1995860) (← links)
• Adaptive LASSO for selecting Fourier coefficients in a functional smooth time-varying cointegrating regression: an application to the Feldstein-Horioka puzzle (Q1998246) (← links)
• Sparse system identification for stochastic systems with general observation sequences (Q2003800) (← links)
• A novel convex clustering method for high-dimensional data using semiproximal ADMM (Q2004149) (← links)
• Sparse principal component analysis via fractional function regularity (Q2007153) (← links)
• Fused variable screening for massive imbalanced data (Q2008001) (← links)
• Time-dependent Poisson reduced rank models for political text data analysis (Q2008098) (← links)
• Solution paths for the generalized Lasso with applications to spatially varying coefficients regression (Q2008112) (← links)
• A nonparametric feature screening method for ultrahigh-dimensional missing response (Q2008122) (← links)
• A Lasso-penalized BIC for mixture model selection (Q2009036) (← links)
• Machine learning subsurface flow equations from data (Q2009819) (← links)
• Robust and efficient estimator for simultaneous model structure identification and variable selection in generalized partial linear varying coefficient models with longitudinal data (Q2010817) (← links)
• A note on quantile feature screening via distance correlation (Q2010823) (← links)
• Efficient regularized regression with \(L_0\) penalty for variable selection and network construction (Q2011726) (← links)
• Partial penalized empirical likelihood ratio test under sparse case (Q2013032) (← links)
• Variable selection for the partial linear single-index model (Q2013035) (← links)
• A robust and efficient estimation and variable selection method for partially linear single-index models (Q2015069) (← links)
• Parametric and semiparametric reduced-rank regression with flexible sparsity (Q2018603) (← links)
• Elastic net penalized quantile regression model (Q2020507) (← links)
• Sparse identification of nonlinear dynamical systems via reweighted \(\ell_1\)-regularized least squares (Q2021994) (← links)
• Consistency bounds and support recovery of d-stationary solutions of sparse sample average approximations (Q2022171) (← links)
• Bayesian MIDAS penalized regressions: estimation, selection, and prediction (Q2024454) (← links)
• Equivalence between adaptive Lasso and generalized ridge estimators in linear regression with orthogonal explanatory variables after optimizing regularization parameters (Q2027229) (← links)
• Simultaneous feature selection and clustering based on square root optimization (Q2028812) (← links)
• A dual reformulation and solution framework for regularized convex clustering problems (Q2029898) (← links)
• Variable selection in partially linear additive hazards model with grouped covariates and a diverging number of parameters (Q2032189) (← links)
• Feature screening based on distance correlation for ultrahigh-dimensional censored data with covariate measurement error (Q2032190) (← links)
• Bayesian bridge-randomized penalized quantile regression for ordinal longitudinal data, with application to firm's bond ratings (Q2032224) (← links)
• Estimation and optimal structure selection of high-dimensional Toeplitz covariance matrix (Q2034455) (← links)
• Minimum average variance estimation with group Lasso for the multivariate response central mean subspace (Q2034465) (← links)
• A cost-sensitive constrained Lasso (Q2036145) (← links)
• Shrinkage estimation of the varying-coefficient model with continuous and categorical covariates (Q2036915) (← links)
• Necessary and sufficient conditions for variable selection consistency of the Lasso in high dimensions (Q2039788) (← links)