The following pages link to (Q3174050):
Displaying 50 items.
- Correlated variables in regression: clustering and sparse estimation (Q394080) (← links)
- Block coordinate descent algorithms for large-scale sparse multiclass classification (Q399900) (← links)
- Shrinkage estimation for identification of linear components in additive models (Q419212) (← links)
- Profiled adaptive elastic-net procedure for partially linear models with high-dimensional covar\-i\-ates (Q419271) (← links)
- Group selection in high-dimensional partially linear additive models (Q424816) (← links)
- Sharp support recovery from noisy random measurements by \(\ell_1\)-minimization (Q427066) (← links)
- Coordinate ascent for penalized semiparametric regression on high-dimensional panel count data (Q429611) (← links)
- Non-convex penalized estimation in high-dimensional models with single-index structure (Q432323) (← links)
- Oracle properties of SCAD-penalized support vector machine (Q433741) (← links)
- Sparse regression learning by aggregation and Langevin Monte-Carlo (Q439987) (← links)
- Mirror averaging with sparsity priors (Q442083) (← links)
- The log-linear group-lasso estimator and its asymptotic properties (Q442085) (← links)
- Transductive versions of the Lasso and the Dantzig selector (Q447611) (← links)
- Estimation in high-dimensional linear models with deterministic design matrices (Q447831) (← links)
- Boosting algorithms: regularization, prediction and model fitting (Q449780) (← links)
- Regularization for Cox's proportional hazards model with NP-dimensionality (Q449987) (← links)
- Learning high-dimensional directed acyclic graphs with latent and selection variables (Q450035) (← links)
- Quadratic approximation on SCAD penalized estimation (Q452598) (← links)
- Sparse regression and support recovery with \(\mathbb{L}_2\)-boosting algorithms (Q466526) (← links)
- Bayesian high-dimensional screening via MCMC (Q466528) (← links)
- Variable selection in infinite-dimensional problems (Q466987) (← links)
- The variational Garrote (Q479478) (← links)
- Covariate assisted screening and estimation (Q482879) (← links)
- A new perspective on least squares under convex constraint (Q482891) (← links)
- CAM: causal additive models, high-dimensional order search and penalized regression (Q482906) (← links)
- High-dimensional Bayesian inference in nonparametric additive models (Q485930) (← links)
- On the residual empirical process based on the ALASSO in high dimensions and its functional oracle property (Q494167) (← links)
- Oracle inequalities for high dimensional vector autoregressions (Q494169) (← links)
- Weighted \(\ell_1\)-penalized corrected quantile regression for high dimensional measurement error models (Q495344) (← links)
- On nonparametric feature filters in electromagnetic imaging (Q499441) (← links)
- Penalized least squares estimation with weakly dependent data (Q525888) (← links)
- Tuning parameter selection for the adaptive LASSO in the autoregressive model (Q526980) (← links)
- Shrinkage tuning parameter selection in precision matrices estimation (Q538141) (← links)
- Improved variable selection with forward-lasso adaptive shrinkage (Q542500) (← links)
- Estimation of high-dimensional low-rank matrices (Q548539) (← links)
- Concentration estimates for learning with \(\ell ^{1}\)-regularizer and data dependent hypothesis spaces (Q550498) (← links)
- Sparse recovery under matrix uncertainty (Q605921) (← links)
- Variable selection and regression analysis for graph-structured covariates with an application to genomics (Q614169) (← links)
- \(\ell_{1}\)-penalization for mixture regression models (Q619141) (← links)
- Consistent group selection in high-dimensional linear regression (Q627307) (← links)
- Adaptive Dantzig density estimation (Q629798) (← links)
- Autoregressive process modeling via the Lasso procedure (Q631620) (← links)
- A majorization-minimization approach to variable selection using spike and slab priors (Q638812) (← links)
- Generalization of constraints for high dimensional regression problems (Q645414) (← links)
- Model selection via adaptive shrinkage with \(t\) priors (Q650694) (← links)
- Parametric or nonparametric? A parametricness index for model selection (Q651025) (← links)
- Factor models and variable selection in high-dimensional regression analysis (Q661163) (← links)
- Generalized M-estimators for high-dimensional Tobit I models (Q668611) (← links)
- Going beyond oracle property: selection consistency and uniqueness of local solution of the generalized linear model (Q670138) (← links)
- Interpreting latent variables in factor models via convex optimization (Q681494) (← links)
