Pages that link to "Item:Q2810910"
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The following pages link to \(L_1\)-regularized least squares for support recovery of high dimensional single index models with Gaussian designs (Q2810910):
Displaying 19 items.
- Sparse Sliced Inverse Regression Via Lasso (Q152378) (← links)
- Isotonic regression meets Lasso (Q668615) (← links)
- Signed support recovery for single index models in high-dimensions (Q679626) (← links)
- Local Walsh-average-based estimation and variable selection for single-index models (Q2010424) (← links)
- Robust parameter estimation of regression models under weakened moment assumptions (Q2081782) (← links)
- Optimal combination of linear and spectral estimators for generalized linear models (Q2088138) (← links)
- Single-index composite quantile regression for ultra-high-dimensional data (Q2161022) (← links)
- Robust post-selection inference of high-dimensional mean regression with heavy-tailed asymmetric or heteroskedastic errors (Q2172011) (← links)
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- (Q5149019) (← links)
- (Q5214246) (← links)
- Estimation of Optimal Individualized Treatment Rules Using a Covariate-Specific Treatment Effect Curve With High-Dimensional Covariates (Q5857150) (← links)
- Discussion on ‘Review of sparse sufficient dimension reduction’ (Q5880038) (← links)
- Distributed Sparse Composite Quantile Regression in Ultrahigh Dimensions (Q6069861) (← links)
- Model-Assisted Uniformly Honest Inference for Optimal Treatment Regimes in High Dimension (Q6107209) (← links)
- Robust inference for high‐dimensional single index models (Q6140331) (← links)
- Just least squares: binary compressive sampling with low generative intrinsic dimension (Q6159304) (← links)
- Understanding Implicit Regularization in Over-Parameterized Single Index Model (Q6185498) (← links)
- A Random Projection Approach to Hypothesis Tests in High-Dimensional Single-Index Models (Q6567896) (← links)
