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.

• Minimax-optimal nonparametric regression in high dimensions (Q2343958) (← links)
• High dimensional single index models (Q2350065) (← links)
• Simultaneous analysis of Lasso and Dantzig selector (Q2388978) (← links)
• Lasso for sparse linear regression with exponentially \(\beta\)-mixing errors (Q2407765) (← links)
• A unified penalized method for sparse additive quantile models: an RKHS approach (Q2409400) (← links)
• Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach (Q2425168) (← links)
• High-dimensional generalized linear models and the lasso (Q2426617) (← links)
• Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators (Q2426826) (← links)
• Support union recovery in high-dimensional multivariate regression (Q2429923) (← links)
• Regression on manifolds: estimation of the exterior derivative (Q2429924) (← links)
• \(\ell_1\)-penalized quantile regression in high-dimensional sparse models (Q2429925) (← links)
• Calibrating nonconvex penalized regression in ultra-high dimension (Q2438760) (← links)
• Estimation and variable selection with exponential weights (Q2447091) (← links)
• Lazy lasso for local regression (Q2512747) (← links)
• Penalised robust estimators for sparse and high-dimensional linear models (Q2664993) (← links)
• Searching for minimal optimal neural networks (Q2667597) (← links)
• High-dimensional robust regression with \(L_q\)-loss functions (Q2674525) (← links)
• A new hybrid \(l_p\)-\(l_2\) model for sparse solutions with applications to image processing (Q2691208) (← links)
• Recovery of partly sparse and dense signals (Q2692936) (← links)
• High-dimensional sparse portfolio selection with nonnegative constraint (Q2700403) (← links)
• On the sparsity of Lasso minimizers in sparse data recovery (Q2700886) (← links)
• \(L_1\)-regularized least squares for support recovery of high dimensional single index models with Gaussian designs (Q2810910) (← links)
• Lasso–type and Heuristic Strategies in Model Selection and Forecasting (Q2829651) (← links)
• Learning sparse classifiers with difference of convex functions algorithms (Q2867410) (← links)
• Estimation for high-dimensional linear mixed-effects models using \(\ell_1\)-penalization (Q2911662) (← links)
• Estimation and variable selection in partial linear single index models with error-prone linear covariates (Q2934843) (← links)
• Non-asymptotic oracle inequalities for the Lasso and Group Lasso in high dimensional logistic model (Q2954238) (← links)
• (Q2958600) (← links)
• Sparse Recovery With Unknown Variance: A LASSO-Type Approach (Q2986269) (← links)
• Variable selection in high-dimensional partly linear additive models (Q3145401) (← links)
• Identifying small mean-reverting portfolios (Q3169214) (← links)
• An Augmented Lagrangian Method for $\ell_{1}$-Regularized Optimization Problems with Orthogonality Constraints (Q3186107) (← links)
• Stability Selection (Q4632639) (← links)
• ORACLE EFFICIENT VARIABLE SELECTION IN RANDOM AND FIXED EFFECTS PANEL DATA MODELS (Q4917233) (← links)
• Understanding large text corpora via sparse machine learning (Q4969899) (← links)
• Two tales of variable selection for high dimensional regression: Screening and model building (Q4969932) (← links)
• Monte Carlo Simulation for Lasso-Type Problems by Estimator Augmentation (Q4975621) (← links)
• Nonbifurcating Phylogenetic Tree Inference via the Adaptive LASSO (Q4999164) (← links)
• The Convex Mixture Distribution: Granger Causality for Categorical Time Series (Q4999347) (← links)
• (Q5004058) (← links)
• Variable Selection With Second-Generation <i>P</i>-Values (Q5050808) (← links)
• (Q5053172) (← links)
• Minimization of $L_1$ Over $L_2$ for Sparse Signal Recovery with Convergence Guarantee (Q5071446) (← links)
• Adaptive elastic net-penalized quantile regression for variable selection (Q5077881) (← links)
• Rates of convergence of the adaptive elastic net and the post-selection procedure in ultra-high dimensional sparse models (Q5079021) (← links)
• Sparse linear regression models of high dimensional covariates with non-Gaussian outliers and Berkson error-in-variable under heteroscedasticity (Q5082770) (← links)
• Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics (Q5083965) (← links)
• On estimation error bounds of the Elastic Net when <i>p</i> ≫ <i>n</i> (Q5089920) (← links)
• Optimal Sparse Linear Prediction for Block-missing Multi-modality Data Without Imputation (Q5120677) (← links)
• (Q5134850) (← links)