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.
- Conditional-quantile screening for ultrahigh-dimensional survival data via martingale difference correlation (Q1989916) (← links)
- Debiasing the Lasso: optimal sample size for Gaussian designs (Q1991670) (← links)
- Measuring and testing for interval quantile dependence (Q1991673) (← links)
- Beyond Gaussian approximation: bootstrap for maxima of sums of independent random vectors (Q1996788) (← links)
- A method for selecting the relevant dimensions for high-dimensional classification in singular vector spaces (Q1999449) (← links)
- Fused variable screening for massive imbalanced data (Q2008001) (← links)
- Feature screening for ultrahigh dimensional categorical data with covariates missing at random (Q2008118) (← links)
- A nonparametric feature screening method for ultrahigh-dimensional missing response (Q2008122) (← links)
- Approximate least squares estimation for spatial autoregressive models with covariates (Q2008130) (← links)
- A note on quantile feature screening via distance correlation (Q2010823) (← links)
- Low-dimensional confounder adjustment and high-dimensional penalized estimation for survival analysis (Q2013304) (← links)
- Determining cutoff point of ensemble trees based on sample size in predicting clinical dose with DNA microarray data (Q2013966) (← links)
- A distribution-based Lasso for a general single-index model (Q2018911) (← links)
- Variable selection for partially linear models via Bayesian subset modeling with diffusing prior (Q2022563) (← links)
- Penalized empirical likelihood for partially linear errors-in-variables panel data models with fixed effects (Q2029210) (← links)
- Feature screening based on distance correlation for ultrahigh-dimensional censored data with covariate measurement error (Q2032190) (← links)
- An efficient algorithm for joint feature screening in ultrahigh-dimensional Cox's model (Q2032191) (← links)
- Inference without compatibility: using exponential weighting for inference on a parameter of a linear model (Q2040072) (← links)
- High-dimensional variable selection via low-dimensional adaptive learning (Q2044323) (← links)
- Learning sparse conditional distribution: an efficient kernel-based approach (Q2044348) (← links)
- Multivariate variable selection by means of null-beamforming (Q2044421) (← links)
- Gini correlation for feature screening (Q2046243) (← links)
- Regularization parameter selection for the low rank matrix recovery (Q2046538) (← links)
- Model-free feature screening via distance correlation for ultrahigh dimensional survival data (Q2062408) (← links)
- Advanced topics in sliced inverse regression (Q2062795) (← links)
- Variable selection in functional regression models: a review (Q2062803) (← links)
- Model-robust subdata selection for big data (Q2063875) (← links)
- Feature screening for ultrahigh-dimensional survival data when failure indicators are missing at random (Q2065267) (← links)
- Sure independence screening in the presence of missing data (Q2066525) (← links)
- Stable correlation and robust feature screening (Q2070420) (← links)
- Projection quantile correlation and its use in high-dimensional grouped variable screening (Q2072410) (← links)
- Conditional screening for ultrahigh-dimensional survival data in case-cohort studies (Q2074082) (← links)
- Broken adaptive ridge regression for right-censored survival data (Q2075449) (← links)
- Fast feature selection via streamwise procedure for massive data (Q2077451) (← links)
- VCSEL: prioritizing SNP-set by penalized variance component selection (Q2078274) (← links)
- Distribution-free and model-free multivariate feature screening via multivariate rank distance correlation (Q2079620) (← links)
- Non-marginal feature screening for varying coefficient competing risks model (Q2081764) (← links)
- Unified mean-variance feature screening for ultrahigh-dimensional regression (Q2095721) (← links)
- Interaction screening via canonical correlation (Q2095771) (← links)
- Model-free global likelihood subsampling for massive data (Q2104012) (← links)
- Revisiting feature selection for linear models with FDR and power guarantees (Q2111958) (← links)
- High-dimensional variable screening through kernel-based conditional mean dependence (Q2112254) (← links)
- Asymptotic properties of high-dimensional random forests (Q2112821) (← links)
- Asset selection based on high frequency Sharpe ratio (Q2116331) (← links)
- Surrogate-variable-based model-free feature screening for survival data under the general censoring mechanism (Q2121452) (← links)
- Interaction identification and clique screening for classification with ultra-high dimensional discrete features (Q2129307) (← links)
- \(\ell_0\)-regularized high-dimensional accelerated failure time model (Q2129574) (← links)
- Nonparametric feature selection by random forests and deep neural networks (Q2129580) (← links)
- RCV-based error density estimation in the ultrahigh dimensional additive model (Q2133638) (← links)
- GSDAR: a fast Newton algorithm for \(\ell_0\) regularized generalized linear models with statistical guarantee (Q2135875) (← links)
