Pages that link to "Item:Q3405559"
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The following pages link to A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article) (Q3405559):
Displaying 50 items.
- (Q4969054) (← links)
- Pruning variable selection ensembles (Q4970243) (← links)
- Variable selection and prediction using a nested, matched case‐control study: Application to hospital acquired pneumonia in stroke patients (Q4979244) (← links)
- (Q4986376) (← links)
- Nonsparse Learning with Latent Variables (Q4994162) (← links)
- (Q4998957) (← links)
- An Efficient Linearly Convergent Regularized Proximal Point Algorithm for Fused Multiple Graphical Lasso Problems (Q4999369) (← links)
- Calibrated zero-norm regularized LS estimator for high-dimensional error-in-variables regression (Q5004050) (← links)
- Penalised empirical likelihood for semiparametric varying-coefficient partially linear errors-in-variables models (Q5012336) (← links)
- A novel bagging approach for variable ranking and selection via a mixed importance measure (Q5036437) (← links)
- Robust feature screening for high-dimensional survival data (Q5036548) (← links)
- Variable selection under multicollinearity using modified log penalty (Q5036976) (← links)
- Bayesian inference in high-dimensional linear models using an empirical correlation-adaptive prior (Q5037803) (← links)
- Sparse Composite Quantile Regression with Ultra-high Dimensional Heterogeneous Data (Q5037835) (← links)
- Using Improved Robust Estimators to Semiparametric Model with High Dimensional Data (Q5050416) (← links)
- <i>L</i><sub>0</sub>-Regularized Learning for High-Dimensional Additive Hazards Regression (Q5058017) (← links)
- Analysis of overfitting in the regularized Cox model (Q5059054) (← links)
- Performance Assessment of High-dimensional Variable Identification (Q5066768) (← links)
- A proximal dual semismooth Newton method for zero-norm penalized quantile regression estimator (Q5066792) (← links)
- Variance ratio screening for ultrahigh dimensional discriminant analysis (Q5075472) (← links)
- Variance estimation for sparse ultra-high dimensional varying coefficient models (Q5078417) (← links)
- In defense of LASSO (Q5081041) (← links)
- Penalized empirical likelihood for generalized linear models with longitudinal data (Q5084007) (← links)
- Exploiting Disagreement Between High-Dimensional Variable Selectors for Uncertainty Visualization (Q5084434) (← links)
- Spike-and-slab type variable selection in the Cox proportional hazards model for high-dimensional features (Q5092986) (← links)
- Asymptotic Theory of \(\boldsymbol \ell _1\) -Regularized PDE Identification from a Single Noisy Trajectory (Q5097857) (← links)
- A model-free feature screening approach based on kernel density estimation (Q5106938) (← links)
- A primal dual active set with continuation algorithm for high-dimensional nonconvex SICA-penalized regression (Q5107360) (← links)
- Wavelet-based LASSO in functional linear quantile regression (Q5107381) (← links)
- Variable selection in joint mean and variance models of Box–Cox transformation (Q5127117) (← links)
- A new variable selection method for uniform designs (Q5129136) (← links)
- Variable selection for partially varying coefficient single-index model (Q5129142) (← links)
- A Bootstrap Lasso + Partial Ridge Method to Construct Confidence Intervals for Parameters in High-dimensional Sparse Linear Models (Q5134479) (← links)
- A Tuning-free Robust and Efficient Approach to High-dimensional Regression (Q5146020) (← links)
- Variable selection in joint location and scale models of the skew-normal distribution (Q5218865) (← links)
- Global sensitivity analysis with dependence measures (Q5220789) (← links)
- Variable selection in regression using maximal correlation and distance correlation (Q5220819) (← links)
- A stepwise regression algorithm for high-dimensional variable selection (Q5220827) (← links)
- Bi-level variable selection via adaptive sparse group Lasso (Q5220909) (← links)
- Application of shrinkage estimation in linear regression models with autoregressive errors (Q5222289) (← links)
- Selective factor extraction in high dimensions (Q5384446) (← links)
- The Lasso for High Dimensional Regression with a Possible Change Point (Q5743231) (← links)
- Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models (Q5743269) (← links)
- Variable Selection Methods in High-dimensional Regression—A Simulation Study (Q5860257) (← links)
- Variance estimation based on blocked 3×2 cross-validation in high-dimensional linear regression (Q5861470) (← links)
- The robust desparsified lasso and the focused information criterion for high-dimensional generalized linear models (Q5880769) (← links)
- Covariate Information Number for Feature Screening in Ultrahigh-Dimensional Supervised Problems (Q5881153) (← links)
- Cellwise outlier detection with false discovery rate control (Q6059406) (← links)
- Efficient multiple change point detection for high‐dimensional generalized linear models (Q6059464) (← links)
- Variable selection for proportional hazards models with high‐dimensional covariates subject to measurement error (Q6059508) (← links)
