Pages that link to "Item:Q1002157"

The following pages link to Lasso-type recovery of sparse representations for high-dimensional data (Q1002157):

Displaying 50 items.

• High-dimensional additive modeling (Q1043712) (← links)
• Model selection consistency of Lasso for empirical data (Q1624086) (← links)
• Variable selection in censored quantile regression with high dimensional data (Q1635848) (← links)
• Lasso, fractional norm and structured sparse estimation using a Hadamard product parametrization (Q1658387) (← links)
• Generalized Kalman smoothing: modeling and algorithms (Q1678609) (← links)
• A doubly sparse approach for group variable selection (Q1680797) (← links)
• A generalized elastic net regularization with smoothed \(\ell _{q}\) penalty for sparse vector recovery (Q1687319) (← links)
• Regularization and the small-ball method. I: Sparse recovery (Q1750281) (← links)
• Recovery of seismic wavefields by an \(l_{q}\)-norm constrained regularization method (Q1785033) (← links)
• Semiparametric efficiency bounds for high-dimensional models (Q1800804) (← links)
• \(\ell _{1}\)-regularized linear regression: persistence and oracle inequalities (Q1930861) (← links)
• PAC-Bayesian estimation and prediction in sparse additive models (Q1951111) (← links)
• On the asymptotic properties of the group lasso estimator for linear models (Q1951765) (← links)
• Honest variable selection in linear and logistic regression models via \(\ell _{1}\) and \(\ell _{1}+\ell _{2}\) penalization (Q1951794) (← links)
• Selection of variables and dimension reduction in high-dimensional non-parametric regression (Q1951796) (← links)
• Thresholding-based iterative selection procedures for model selection and shrinkage (Q1951984) (← links)
• On the conditions used to prove oracle results for the Lasso (Q1952029) (← links)
• MAP model selection in Gaussian regression (Q1952087) (← links)
• The Lasso as an \(\ell _{1}\)-ball model selection procedure (Q1952205) (← links)
• The adaptive and the thresholded Lasso for potentially misspecified models (and a lower bound for the Lasso) (Q1952206) (← links)
• The smooth-Lasso and other \(\ell _{1}+\ell _{2}\)-penalized methods (Q1952223) (← links)
• Least squares after model selection in high-dimensional sparse models (Q1952433) (← links)
• Sign-constrained least squares estimation for high-dimensional regression (Q1954143) (← links)
• Inference under Fine-Gray competing risks model with high-dimensional covariates (Q2008618) (← links)
• Greedy variance estimation for the LASSO (Q2019914) (← links)
• Consistent multiple changepoint estimation with fused Gaussian graphical models (Q2042434) (← links)
• Multicarving for high-dimensional post-selection inference (Q2044355) (← links)
• Graphical-model based high dimensional generalized linear models (Q2044367) (← links)
• A sparse optimization problem with hybrid \(L_2\)-\(L_p\) regularization for application of magnetic resonance brain images (Q2060052) (← links)
• Model-robust subdata selection for big data (Q2063875) (← links)
• Provable training set debugging for linear regression (Q2071505) (← links)
• Feature selection for data integration with mixed multiview data (Q2078739) (← links)
• Multivariate sparse Laplacian shrinkage for joint estimation of two graphical structures (Q2101407) (← links)
• Sparse spatio-temporal autoregressions by profiling and bagging (Q2106397) (← links)
• Nonparametric and high-dimensional functional graphical models (Q2106795) (← links)
• Sparse Laplacian shrinkage with the graphical Lasso estimator for regression problems (Q2125484) (← links)
• Ridge regression revisited: debiasing, thresholding and bootstrap (Q2148980) (← links)
• Robust machine learning by median-of-means: theory and practice (Q2196199) (← links)
• A two-step method for estimating high-dimensional Gaussian graphical models (Q2197843) (← links)
• Which bridge estimator is the best for variable selection? (Q2215760) (← links)
• Detecting groups in large vector autoregressions (Q2236879) (← links)
• Pivotal estimation via square-root lasso in nonparametric regression (Q2249850) (← links)
• High-dimensional mean estimation via \(\ell_1\) penalized normal likelihood (Q2252887) (← links)
• High-dimensional variable screening and bias in subsequent inference, with an empirical comparison (Q2259726) (← links)
• A global homogeneity test for high-dimensional linear regression (Q2263711) (← links)
• Consistency of Bayesian linear model selection with a growing number of parameters (Q2276179) (← links)
• Ultrahigh dimensional precision matrix estimation via refitted cross validation (Q2295804) (← links)
• A review of Gaussian Markov models for conditional independence (Q2301082) (← links)
• Fuzzy Lasso regression model with exact explanatory variables and fuzzy responses (Q2302823) (← links)
• Structured estimation for the nonparametric Cox model (Q2340869) (← links)