Pages that link to "Item:Q4632602"

The following pages link to Sure Independence Screening for Ultrahigh Dimensional Feature Space (Q4632602):

Displaying 50 items.

• A general framework for tensor screening through smoothing (Q2136613) (← links)
• On sufficient variable screening using log odds ratio filter (Q2136614) (← links)
• New hard-thresholding rules based on data splitting in high-dimensional imbalanced classification (Q2136627) (← links)
• Post-model-selection inference in linear regression models: an integrated review (Q2137823) (← links)
• Variable screening for varying coefficient models with ultrahigh-dimensional survival data (Q2143009) (← links)
• Mallows model averaging with effective model size in fragmentary data prediction (Q2143019) (← links)
• Feature screening and FDR control with knockoff features for ultrahigh-dimensional right-censored data (Q2143024) (← links)
• Robust error density estimation in ultrahigh dimensional sparse linear model (Q2150677) (← links)
• On LASSO for predictive regression (Q2155298) (← links)
• Bayesian factor-adjusted sparse regression (Q2155305) (← links)
• High-dimensional causal mediation analysis based on partial linear structural equation models (Q2157518) (← links)
• A data-driven line search rule for support recovery in high-dimensional data analysis (Q2157522) (← links)
• Independence index sufficient variable screening for categorical responses (Q2157537) (← links)
• The backbone method for ultra-high dimensional sparse machine learning (Q2163249) (← links)
• Robust post-selection inference of high-dimensional mean regression with heavy-tailed asymmetric or heteroskedastic errors (Q2172011) (← links)
• Polya tree-based nearest neighborhood regression (Q2172106) (← links)
• Robust change point detection method via adaptive LAD-Lasso (Q2175643) (← links)
• Model-free conditional screening via conditional distance correlation (Q2175650) (← links)
• Statistical inference for model parameters in stochastic gradient descent (Q2176618) (← links)
• Feature selection for generalized varying coefficient mixed-effect models with application to obesity GWAS (Q2179968) (← links)
• Nonconcave penalized estimation in sparse vector autoregression model (Q2180066) (← links)
• Joint model-free feature screening for ultra-high dimensional semi-competing risks data (Q2181545) (← links)
• Model-free feature screening for ultrahigh dimensional classification (Q2181726) (← links)
• Nonparametric variable selection and its application to additive models (Q2183769) (← links)
• Projective inference in high-dimensional problems: prediction and feature selection (Q2188473) (← links)
• Feature screening under missing indicator imputation with non-ignorable missing response (Q2189600) (← links)
• Bayesian variable selection for survival data using inverse moment priors (Q2194467) (← links)
• Uniform joint screening for ultra-high dimensional graphical models (Q2196128) (← links)
• GRID: a variable selection and structure discovery method for high dimensional nonparametric regression (Q2196249) (← links)
• A two-step method for estimating high-dimensional Gaussian graphical models (Q2197843) (← links)
• Sequential feature screening for generalized linear models with sparse ultra-high dimensional data (Q2200110) (← links)
• Block-regularized repeated learning-testing for estimating generalization error (Q2201671) (← links)
• Robust composite weighted quantile screening for ultrahigh dimensional discriminant analysis (Q2202032) (← links)
• Ultra-high dimensional variable screening via Gram-Schmidt orthogonalization (Q2203408) (← links)
• Conditional SIRS for nonparametric and semiparametric models by marginal empirical likelihood (Q2208382) (← links)
• A robust and efficient estimation and variable selection method for partially linear models with large-dimensional covariates (Q2208404) (← links)
• Model selection for high-dimensional linear regression with dependent observations (Q2215720) (← links)
• Which bridge estimator is the best for variable selection? (Q2215760) (← links)
• Exact tests via multiple data splitting (Q2216942) (← links)
• Dynamic tilted current correlation for high dimensional variable screening (Q2222224) (← links)
• Consistent group selection with Bayesian high dimensional modeling (Q2226716) (← links)
• Variable importance assessments and backward variable selection for multi-sample problems (Q2237823) (← links)
• Composite quantile regression for ultra-high dimensional semiparametric model averaging (Q2242007) (← links)
• Robust communication-efficient distributed composite quantile regression and variable selection for massive data (Q2242035) (← links)
• Feature filter for estimating central mean subspace and its sparse solution (Q2242163) (← links)
• A sequential approach to feature selection in high-dimensional additive models (Q2242862) (← links)
• Testing regression coefficients in high-dimensional and sparse settings (Q2244668) (← links)
• The fused Kolmogorov-Smirnov screening for ultra-high dimensional semi-competing risks data (Q2247336) (← links)
• Sparse and efficient estimation for partial spline models with increasing dimension (Q2255168) (← links)
• High-dimensional variable screening and bias in subsequent inference, with an empirical comparison (Q2259726) (← links)