Pages that link to "Item:Q2664993"
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The following pages link to Penalised robust estimators for sparse and high-dimensional linear models (Q2664993):
Displaying 20 items.
- High dimensional robust M-estimation: asymptotic variance via approximate message passing (Q343797) (← links)
- Robustness in sparse high-dimensional linear models: relative efficiency and robust approximate message passing (Q502845) (← links)
- M-estimation in high-dimensional linear model (Q824747) (← links)
- A general family of trimmed estimators for robust high-dimensional data analysis (Q1616324) (← links)
- Robust and sparse estimators for linear regression models (Q1654238) (← links)
- Wavelet-based robust estimation and variable selection in nonparametric additive models (Q2066754) (← links)
- Robust subset selection (Q2076115) (← links)
- Penalized robust estimators in sparse logistic regression (Q2084709) (← links)
- Penalized wavelet estimation and robust denoising for irregular spaced data (Q2095705) (← links)
- Large-scale regression with non-convex loss and penalty (Q2192647) (← links)
- Ultrahigh dimensional variable selection through the penalized maximum trimmed likelihood estimator (Q2442684) (← links)
- Sparse estimation via lower-order penalty optimization methods in high-dimensional linear regression (Q2687439) (← links)
- On robust regression with high-dimensional predictors (Q2962135) (← links)
- Approximate separability of symmetrically penalized least squares in high dimensions: characterization and consequences (Q3383825) (← links)
- M-estimation and model identification based on double SCAD penalization (Q5075480) (← links)
- Sparse linear regression models of high dimensional covariates with non-Gaussian outliers and Berkson error-in-variable under heteroscedasticity (Q5082770) (← links)
- Robust Sparse Regression with High-Breakdown Value (Q5259110) (← links)
- Simultaneous feature selection and outlier detection with optimality guarantees (Q6055709) (← links)
- Robust statistical boosting with quantile-based adaptive loss functions (Q6636211) (← links)
- Bootstrap estimation of the proportion of outliers in robust regression (Q6657838) (← links)
