Pages that link to "Item:Q4632602"
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The following pages link to Sure Independence Screening for Ultrahigh Dimensional Feature Space (Q4632602):
Displaying 50 items.
- On the distance concentration awareness of certain data reduction techniques (Q614077) (← links)
- On model selection from a finite family of possibly misspecified time series models (Q666592) (← links)
- Joint adaptive mean-variance regularization and variance stabilization of high dimensional data (Q693237) (← links)
- Variable selection after screening: with or without data splitting? (Q737000) (← links)
- Empirical likelihood for a varying coefficient partially linear model with diverging number of parameters (Q764476) (← links)
- Principled sure independence screening for Cox models with ultra-high-dimensional covariates (Q764508) (← links)
- Sparse hierarchical regression with polynomials (Q782451) (← links)
- A shrinkage principle for heavy-tailed data: high-dimensional robust low-rank matrix recovery (Q820791) (← links)
- Conditional distance correlation screening for sparse ultrahigh-dimensional models (Q821654) (← links)
- Forward variable selection for sparse ultra-high-dimensional generalized varying coefficient models (Q825321) (← links)
- An attention algorithm for solving large scale structured \(l_0\)-norm penalty estimation problems (Q825333) (← links)
- Fitting sparse linear models under the sufficient and necessary condition for model identification (Q826666) (← links)
- Maximum-type tests for high-dimensional regression coefficients using Wilcoxon scores (Q826977) (← links)
- Censored mean variance sure independence screening for ultrahigh dimensional survival data (Q830110) (← links)
- A nonparametric empirical Bayes approach to large-scale multivariate regression (Q830438) (← links)
- Partition-based feature screening for categorical data via RKHS embeddings (Q830506) (← links)
- Model-free variable selection for conditional mean in regression (Q830544) (← links)
- Hybrid safe-strong rules for efficient optimization in Lasso-type problems (Q830584) (← links)
- Group orthogonal greedy algorithm for change-point estimation of multivariate time series (Q830674) (← links)
- A scalable surrogate \(L_0\) sparse regression method for generalized linear models with applications to large scale data (Q830734) (← links)
- A selective overview of feature screening for ultrahigh-dimensional data (Q892795) (← links)
- Dimension reduction based linear surrogate variable approach for model free variable selection (Q900762) (← links)
- Robust model-free feature screening via quantile correlation (Q900833) (← links)
- Testing covariates in high dimension linear regression with latent factors (Q901275) (← links)
- Independent rule in classification of multivariate binary data (Q1036789) (← links)
- Nonparametric feature screening (Q1615096) (← links)
- On selecting interacting features from high-dimensional data (Q1621350) (← links)
- Using random subspace method for prediction and variable importance assessment in linear regression (Q1621353) (← links)
- LOL selection in high dimension (Q1621355) (← links)
- Group subset selection for linear regression (Q1623472) (← links)
- A sequential test for variable selection in high dimensional complex data (Q1623732) (← links)
- Network-based feature screening with applications to genome data (Q1624846) (← links)
- Individual-level social influence identification in social media: a learning-simulation coordinated method (Q1631522) (← links)
- Variable selection in censored quantile regression with high dimensional data (Q1635848) (← links)
- Robust dependence measure for detecting associations in large data set (Q1636995) (← links)
- Conditional feature screening for mean and variance functions in models with multiple-index structure (Q1639572) (← links)
- Censored cumulative residual independent screening for ultrahigh-dimensional survival data (Q1642144) (← links)
- Nonparametric independence screening via favored smoothing bandwidth (Q1643789) (← links)
- Conditional quantile correlation screening procedure for ultrahigh-dimensional varying coefficient models (Q1643796) (← links)
- Powerful test based on conditional effects for genome-wide screening (Q1647641) (← links)
- Test for high-dimensional regression coefficients using refitted cross-validation variance estimation (Q1650066) (← links)
- Screening group variables in the proportional hazards model (Q1650285) (← links)
- Ultrahigh dimensional feature screening via projection (Q1658358) (← links)
- Two-layer EM algorithm for ALD mixture regression models: a new solution to composite quantile regression (Q1658381) (← links)
- Principal components adjusted variable screening (Q1658427) (← links)
- Correlation rank screening for ultrahigh-dimensional survival data (Q1658466) (← links)
- Variable selection using shrinkage priors (Q1658484) (← links)
- Canonical kernel dimension reduction (Q1658489) (← links)
- Model free feature screening for ultrahigh dimensional data with responses missing at random (Q1658537) (← links)
- Feature screening for generalized varying coefficient models with application to dichotomous responses (Q1659028) (← links)
