The following pages link to Scaled sparse linear regression (Q3143465):
Displaying 50 items.
- On asymptotically optimal confidence regions and tests for high-dimensional models (Q95759) (← links)
- Tuning-Free Heterogeneity Pursuit in Massive Networks (Q148592) (← links)
- Asymptotic normality and optimalities in estimation of large Gaussian graphical models (Q152845) (← links)
- Gaussian graphical model estimation with false discovery rate control (Q152850) (← links)
- Confidence intervals for high-dimensional partially linear single-index models (Q290693) (← links)
- Matrix completion via max-norm constrained optimization (Q302432) (← links)
- On estimation of the diagonal elements of a sparse precision matrix (Q302437) (← links)
- The benefit of group sparsity in group inference with de-biased scaled group Lasso (Q309547) (← links)
- Testing a single regression coefficient in high dimensional linear models (Q311657) (← links)
- Regression analysis for microbiome compositional data (Q312961) (← links)
- AIC for the Lasso in generalized linear models (Q315399) (← links)
- Optimal equivariant prediction for high-dimensional linear models with arbitrary predictor covariance (Q358878) (← links)
- Statistical significance in high-dimensional linear models (Q373525) (← links)
- Non-negative least squares for high-dimensional linear models: consistency and sparse recovery without regularization (Q391843) (← links)
- Correlated variables in regression: clustering and sparse estimation (Q394080) (← links)
- Sparse estimation from noisy observations of an overdetermined linear system (Q473308) (← links)
- Covariate assisted screening and estimation (Q482879) (← links)
- Selecting massive variables using an iterated conditional modes/medians algorithm (Q491389) (← links)
- Sparse regression using mixed norms (Q734328) (← links)
- Sparse hierarchical regression with polynomials (Q782451) (← links)
- Adaptive robust estimation in sparse vector model (Q820801) (← links)
- A self-calibrated direct approach to precision matrix estimation and linear discriminant analysis in high dimensions (Q829737) (← links)
- A nonparametric empirical Bayes approach to large-scale multivariate regression (Q830438) (← links)
- Finite mixture regression: a sparse variable selection by model selection for clustering (Q902208) (← links)
- SLOPE-adaptive variable selection via convex optimization (Q902886) (← links)
- Edge detection in sparse Gaussian graphical models (Q1615220) (← links)
- Significance testing in non-sparse high-dimensional linear models (Q1616315) (← links)
- On the prediction loss of the Lasso in the partially labeled setting (Q1616320) (← links)
- Kernel-penalized regression for analysis of microbiome data (Q1647639) (← links)
- High-dimensional multivariate posterior consistency under global-local shrinkage priors (Q1661340) (← links)
- Balanced estimation for high-dimensional measurement error models (Q1663093) (← links)
- Confidence regions for entries of a large precision matrix (Q1668572) (← links)
- Linear regression with sparsely permuted data (Q1711600) (← links)
- Oracle inequalities for high-dimensional prediction (Q1740524) (← links)
- Improved bounds for square-root Lasso and square-root slope (Q1746538) (← links)
- Optimal bounds for aggregation of affine estimators (Q1747732) (← links)
- Adaptive estimation of high-dimensional signal-to-noise ratios (Q1750099) (← links)
- Selective inference with a randomized response (Q1750283) (← links)
- High-dimensional inference: confidence intervals, \(p\)-values and R-software \texttt{hdi} (Q1790302) (← links)
- On the exponentially weighted aggregate with the Laplace prior (Q1800807) (← links)
- Debiasing the Lasso: optimal sample size for Gaussian designs (Q1991670) (← links)
- Inference without compatibility: using exponential weighting for inference on a parameter of a linear model (Q2040072) (← links)
- Iteratively reweighted \(\ell_1\)-penalized robust regression (Q2044416) (← links)
- Evaluating visual properties via robust HodgeRank (Q2054405) (← links)
- Second-order Stein: SURE for SURE and other applications in high-dimensional inference (Q2054467) (← links)
- Comparing six shrinkage estimators with large sample theory and asymptotically optimal prediction intervals (Q2062391) (← links)
- In defense of the indefensible: a very naïve approach to high-dimensional inference (Q2075709) (← links)
- Two-sample testing of high-dimensional linear regression coefficients via complementary sketching (Q2105203) (← links)
- Improved estimators for semi-supervised high-dimensional regression model (Q2106769) (← links)
- De-biasing the Lasso with degrees-of-freedom adjustment (Q2136990) (← links)
