Pages that link to "Item:Q5220866"
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The following pages link to An iterative approach to distance correlation-based sure independence screening (Q5220866):
Displaying 19 items.
- Feature screening based on distance correlation for ultrahigh-dimensional censored data with covariate measurement error (Q2032190) (← links)
- The exact equivalence of distance and kernel methods in hypothesis testing (Q2058548) (← links)
- Distribution-free and model-free multivariate feature screening via multivariate rank distance correlation (Q2079620) (← links)
- A sequential approach to feature selection in high-dimensional additive models (Q2242862) (← links)
- Screening and selection for quantile regression using an alternative measure of variable importance (Q2274955) (← links)
- Grouped variable screening for ultra-high dimensional data for linear model (Q2291335) (← links)
- On a Screened Pearson Correlation and Its Application to Interdependence Methods (Q4648643) (← links)
- Projection correlation between scalar and vector variables and its use in feature screening with multi-response data (Q5036832) (← links)
- The Chi-Square Test of Distance Correlation (Q5083373) (← links)
- Model-Free Forward Screening Via Cumulative Divergence (Q5120676) (← links)
- Composite Coefficient of Determination and Its Application in Ultrahigh Dimensional Variable Screening (Q5208077) (← links)
- A Generic Sure Independence Screening Procedure (Q5231519) (← links)
- Group screening for ultra-high-dimensional feature under linear model (Q5880025) (← links)
- Covariate Information Number for Feature Screening in Ultrahigh-Dimensional Supervised Problems (Q5881153) (← links)
- Model-free, monotone invariant and computationally efficient feature screening with data-adaptive threshold (Q6049410) (← links)
- Portfolio selection based on semivariance and distance correlation under minimum variance framework (Q6067644) (← links)
- RaSE: A Variable Screening Framework via Random Subspace Ensembles (Q6107221) (← links)
- Calibrating multi-dimensional complex ODE from noisy data via deep neural networks (Q6556771) (← links)
- Universally consistent \(\mathrm{K}\)-sample tests via dependence measures (Q6650768) (← links)
