Pages that link to "Item:Q2388978"

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

Displaying 50 items.

• Estimator selection with respect to Hellinger-type risks (Q644788) (← links)
• Generalization of constraints for high dimensional regression problems (Q645414) (← links)
• Oracle inequalities and optimal inference under group sparsity (Q651028) (← links)
• Support vector machines with a reject option (Q654412) (← links)
• Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion (Q661157) (← links)
• Factor models and variable selection in high-dimensional regression analysis (Q661163) (← links)
• On model selection from a finite family of possibly misspecified time series models (Q666592) (← links)
• Generalized M-estimators for high-dimensional Tobit I models (Q668611) (← links)
• Isotonic regression meets Lasso (Q668615) (← links)
• High-dimensional regression with noisy and missing data: provable guarantees with nonconvexity (Q693741) (← links)
• SOCP based variance free Dantzig selector with application to robust estimation (Q715639) (← links)
• Solution of linear ill-posed problems using random dictionaries (Q721620) (← links)
• Sparse factor regression via penalized maximum likelihood estimation (Q725684) (← links)
• Some theoretical results on the grouped variables Lasso (Q734551) (← links)
• Joint variable and rank selection for parsimonious estimation of high-dimensional matrices (Q741790) (← links)
• Fast global convergence of gradient methods for high-dimensional statistical recovery (Q741793) (← links)
• Regularized rank-based estimation of high-dimensional nonparanormal graphical models (Q741796) (← links)
• Accuracy guaranties for \(\ell_{1}\) recovery of block-sparse signals (Q741817) (← links)
• Model selection by LASSO methods in a change-point model (Q744757) (← links)
• Penalized estimation in additive varying coefficient models using grouped regularization (Q744806) (← links)
• Prediction-based regularization using data augmented regression (Q746200) (← links)
• Spline estimator for simultaneous variable selection and constant coefficient identification in high-dimensional generalized varying-coefficient models (Q746868) (← links)
• The \(\ell_{2,q}\) regularized group sparse optimization: lower bound theory, recovery bound and algorithms (Q778013) (← links)
• High-dimensional model recovery from random sketched data by exploring intrinsic sparsity (Q782446) (← links)
• A shrinkage principle for heavy-tailed data: high-dimensional robust low-rank matrix recovery (Q820791) (← links)
• On cross-validated Lasso in high dimensions (Q820794) (← links)
• Statistical inference in sparse high-dimensional additive models (Q820814) (← links)
• Lasso-driven inference in time and space (Q820826) (← links)
• Fitting sparse linear models under the sufficient and necessary condition for model identification (Q826666) (← links)
• High dimensional regression for regenerative time-series: an application to road traffic modeling (Q830094) (← links)
• A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model (Q830540) (← links)
• Sparse recovery via nonconvex regularized \(M\)-estimators over \(\ell_q\)-balls (Q830557) (← links)
• Some sharp performance bounds for least squares regression with \(L_1\) regularization (Q834334) (← links)
• Near-ideal model selection by \(\ell _{1}\) minimization (Q834335) (← links)
• LASSO estimation of threshold autoregressive models (Q888321) (← links)
• Bayesian linear regression with sparse priors (Q888501) (← links)
• Controlling the false discovery rate via knockoffs (Q888503) (← links)
• Efficient nonconvex sparse group feature selection via continuous and discrete optimization (Q892230) (← links)
• Model selection and structure specification in ultra-high dimensional generalised semi-varying coefficient models (Q892254) (← links)
• Lasso-type estimators for semiparametric nonlinear mixed-effects models estimation (Q892492) (← links)
• Stability of the elastic net estimator (Q895982) (← links)
• \(\ell_1\)-regularization of high-dimensional time-series models with non-Gaussian and heteroskedastic errors (Q898600) (← links)
• Sampling in the analysis transform domain (Q900778) (← links)
• Nonconvex penalized reduced rank regression and its oracle properties in high dimensions (Q900821) (← links)
• Finite mixture regression: a sparse variable selection by model selection for clustering (Q902208) (← links)
• High-dimensional Gaussian model selection on a Gaussian design (Q985331) (← links)
• The benefit of group sparsity (Q987996) (← links)
• SPADES and mixture models (Q988014) (← links)
• Lasso-type recovery of sparse representations for high-dimensional data (Q1002157) (← links)
• Aggregation by exponential weighting, sharp PAC-Bayesian bounds and sparsity (Q1009266) (← links)