The following pages link to (Q4864293):
Displaying 50 items.
- On Bayesian lasso variable selection and the specification of the shrinkage parameter (Q746286) (← links)
- A tutorial on rank-based coefficient estimation for censored data in small- and large-scale problems (Q746299) (← links)
- Random effects selection in generalized linear mixed models via shrinkage penalty function (Q746316) (← links)
- Shrinkage estimation of varying covariate effects based on quantile regression (Q746335) (← links)
- Majorization minimization by coordinate descent for concave penalized generalized linear models (Q746337) (← links)
- Another look at linear programming for feature selection via methods of regularization (Q746339) (← links)
- Edge selection based on the geometry of dually flat spaces for Gaussian graphical models (Q746349) (← links)
- Bayesian group Lasso for nonparametric varying-coefficient models with application to functional genome-wide association studies (Q746650) (← links)
- Multi-species distribution modeling using penalized mixture of regressions (Q746675) (← links)
- Sample size determination for training cancer classifiers from microarray and RNA-seq data (Q746699) (← links)
- Wavelet-domain regression and predictive inference in psychiatric neuroimaging (Q746704) (← links)
- Quantile regression for dynamic partially linear varying coefficient time series models (Q746867) (← links)
- Spline estimator for simultaneous variable selection and constant coefficient identification in high-dimensional generalized varying-coefficient models (Q746868) (← links)
- Convex relaxations of penalties for sparse correlated variables with bounded total variation (Q747277) (← links)
- LASSO-based multivariate linear profile monitoring (Q763195) (← links)
- Variable selection using penalized empirical likelihood (Q763671) (← links)
- Sparse estimation in functional linear regression (Q764470) (← links)
- Principled sure independence screening for Cox models with ultra-high-dimensional covariates (Q764508) (← links)
- Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data (Q764510) (← links)
- Information, data dimension and factor structure (Q765833) (← links)
- Sparse approximations of protein structure from noisy random projections (Q765999) (← links)
- An easy-to-implement hierarchical standardization for variable selection under strong heredity constraint (Q777839) (← links)
- The \(\ell_{2,q}\) regularized group sparse optimization: lower bound theory, recovery bound and algorithms (Q778013) (← links)
- Preserving injectivity under subgaussian mappings and its application to compressed sensing (Q778017) (← links)
- Efficient parameter estimation and variable selection in partial linear varying coefficient quantile regression model with longitudinal data (Q779677) (← links)
- Variable selection for spatial autoregressive models with a diverging number of parameters (Q779691) (← links)
- Application of a new accelerated algorithm to regression problems (Q780302) (← links)
- Sparse regression with output correlation for cardiac ejection fraction estimation (Q781053) (← links)
- Generalized ADMM with optimal indefinite proximal term for linearly constrained convex optimization (Q781096) (← links)
- A constrained least squares regression model (Q781860) (← links)
- Locally linear ensemble for regression (Q781904) (← links)
- Sparse polynomial chaos expansions using variational relevance vector machines (Q781971) (← links)
- High-dimensional model recovery from random sketched data by exploring intrinsic sparsity (Q782446) (← links)
- Sparse hierarchical regression with polynomials (Q782451) (← links)
- Simple Poisson PCA: an algorithm for (sparse) feature extraction with simultaneous dimension determination (Q782631) (← links)
- Convergence study of indefinite proximal ADMM with a relaxation factor (Q782911) (← links)
- Stable portfolio selection strategy for mean-variance-CVaR model under high-dimensional scenarios (Q783138) (← links)
- A shrinkage principle for heavy-tailed data: high-dimensional robust low-rank matrix recovery (Q820791) (← links)
- On cross-validated Lasso in high dimensions (Q820794) (← links)
- Conditional distance correlation screening for sparse ultrahigh-dimensional models (Q821654) (← links)
- Adaptive and reversed penalty for analysis of high-dimensional correlated data (Q823261) (← links)
- Single- and multiple-group penalized factor analysis: a trust-region algorithm approach with integrated automatic multiple tuning parameter selection (Q823858) (← links)
- On the quantification of model uncertainty: a Bayesian perspective (Q823871) (← links)
- Forward variable selection for sparse ultra-high-dimensional generalized varying coefficient models (Q825321) (← links)
- Fitting sparse linear models under the sufficient and necessary condition for model identification (Q826666) (← links)
- Endogenous treatment effect estimation using high-dimensional instruments and double selection (Q826717) (← links)
- The effect of regularization in portfolio selection problems (Q828760) (← links)
- Nonsmoothness in machine learning: specific structure, proximal identification, and applications (Q829492) (← links)
- MM algorithms for distance covariance based sufficient dimension reduction and sufficient variable selection (Q829724) (← links)
- Robust variable selection with exponential squared loss for the spatial autoregressive model (Q829731) (← links)
