The following pages link to (Q3174050):
Displaying 50 items.
- On the conditions used to prove oracle results for the Lasso (Q1952029) (← links)
- Self-concordant analysis for logistic regression (Q1952060) (← links)
- Sparse regression with exact clustering (Q1952092) (← links)
- Adaptive estimation of covariance matrices via Cholesky decomposition (Q1952094) (← links)
- The Lasso as an \(\ell _{1}\)-ball model selection procedure (Q1952205) (← links)
- The adaptive and the thresholded Lasso for potentially misspecified models (and a lower bound for the Lasso) (Q1952206) (← links)
- High-dimensional covariance estimation by minimizing \(\ell _{1}\)-penalized log-determinant divergence (Q1952214) (← links)
- Robust regression through the Huber's criterion and adaptive lasso penalty (Q1952217) (← links)
- The smooth-Lasso and other \(\ell _{1}+\ell _{2}\)-penalized methods (Q1952223) (← links)
- Least squares after model selection in high-dimensional sparse models (Q1952433) (← links)
- A partially proximal linearized alternating minimization method for finding Dantzig selectors (Q1983897) (← links)
- A new scope of penalized empirical likelihood with high-dimensional estimating equations (Q1990574) (← links)
- Sparse system identification for stochastic systems with general observation sequences (Q2003800) (← links)
- Sparse principal component based high-dimensional mediation analysis (Q2008127) (← links)
- Rate optimal estimation and confidence intervals for high-dimensional regression with missing covariates (Q2008214) (← links)
- Adaptive group Lasso for high-dimensional generalized linear models (Q2010806) (← links)
- Parametric and semiparametric reduced-rank regression with flexible sparsity (Q2018603) (← links)
- A distribution-based Lasso for a general single-index model (Q2018911) (← links)
- Consistency bounds and support recovery of d-stationary solutions of sparse sample average approximations (Q2022171) (← links)
- Simultaneous feature selection and clustering based on square root optimization (Q2028812) (← links)
- Variable selection in partially linear additive hazards model with grouped covariates and a diverging number of parameters (Q2032189) (← links)
- An efficient algorithm for joint feature screening in ultrahigh-dimensional Cox's model (Q2032191) (← links)
- Estimation and optimal structure selection of high-dimensional Toeplitz covariance matrix (Q2034455) (← links)
- A unified primal dual active set algorithm for nonconvex sparse recovery (Q2038299) (← links)
- Robust high-dimensional factor models with applications to statistical machine learning (Q2038305) (← links)
- Necessary and sufficient conditions for variable selection consistency of the Lasso in high dimensions (Q2039788) (← links)
- High-dimensional variable selection via low-dimensional adaptive learning (Q2044323) (← links)
- Graphical-model based high dimensional generalized linear models (Q2044367) (← links)
- Iteratively reweighted \(\ell_1\)-penalized robust regression (Q2044416) (← links)
- Adaptive function-on-scalar regression with a smoothing elastic net (Q2048111) (← links)
- \(\ell_{2,0}\)-norm based selection and estimation for multivariate generalized linear models (Q2048127) (← links)
- Evaluating visual properties via robust HodgeRank (Q2054405) (← links)
- Second-order Stein: SURE for SURE and other applications in high-dimensional inference (Q2054467) (← links)
- Prediction bounds for higher order total variation regularized least squares (Q2054527) (← links)
- High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood (Q2058896) (← links)
- Comparing six shrinkage estimators with large sample theory and asymptotically optimal prediction intervals (Q2062391) (← links)
- Nonnegative estimation and variable selection under minimax concave penalty for sparse high-dimensional linear regression models (Q2066516) (← links)
- Optimal linear discriminators for the discrete choice model in growing dimensions (Q2073710) (← links)
- In defense of the indefensible: a very naïve approach to high-dimensional inference (Q2075709) (← links)
- Robust subset selection (Q2076115) (← links)
- Smoothly adaptively centered ridge estimator (Q2078549) (← links)
- Feature selection for data integration with mixed multiview data (Q2078739) (← links)
- Network differential connectivity analysis (Q2080732) (← links)
- Variable selection in convex quantile regression: \(\mathcal{L}_1\)-norm or \(\mathcal{L}_0\)-norm regularization? (Q2083962) (← links)
- Lasso regression and its application in forecasting macro economic indicators: a study on Vietnam's exports (Q2086244) (← links)
- Robust moderately clipped LASSO for simultaneous outlier detection and variable selection (Q2091331) (← links)
- Information criteria bias correction for group selection (Q2093122) (← links)
- Penalized wavelet estimation and robust denoising for irregular spaced data (Q2095705) (← links)
- High-dimensional linear regression with hard thresholding regularization: theory and algorithm (Q2097492) (← links)
- Sparse regression at scale: branch-and-bound rooted in first-order optimization (Q2097642) (← links)
