Pages that link to "Item:Q5962732"

The following pages link to Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors (Q5962732):

Displaying 43 items.

• A primal dual active set with continuation algorithm for high-dimensional nonconvex SICA-penalized regression (Q5107360) (← links)
• Mechanism and a new algorithm for nonconvex clustering (Q5107735) (← links)
• Principal single-index varying-coefficient models for dimension reduction in quantile regression (Q5107741) (← links)
• Modeling Between-Study Heterogeneity for Improved Replicability in Gene Signature Selection and Clinical Prediction (Q5120652) (← links)
• Multi-Armed Angle-Based Direct Learning for Estimating Optimal Individualized Treatment Rules With Various Outcomes (Q5130612) (← links)
• Designing Patient-Specific Optimal Neurostimulation Patterns for Seizure Suppression (Q5157172) (← links)
• Iteratively Reweighted Group Lasso Based on Log-Composite Regularization (Q5161764) (← links)
• Principal varying coefficient estimator for high-dimensional models (Q5205848) (← links)
• Computation of second-order directional stationary points for group sparse optimization (Q5210743) (← links)
• Sparse optimization for nonconvex group penalized estimation (Q5222360) (← links)
• Structural identification and variable selection in high-dimensional varying-coefficient models (Q5266564) (← links)
• A lower bound based smoothed quasi-Newton algorithm for group bridge penalized regression (Q5373886) (← links)
• Estimating DNA methylation levels by joint modeling of multiple methylation profiles from microarray data (Q5739257) (← links)
• Group Sparse Optimization for Images Recovery Using Capped Folded Concave Functions (Q5860273) (← links)
• Group screening for ultra-high-dimensional feature under linear model (Q5880025) (← links)
• Spike-and-Slab Group Lassos for Grouped Regression and Sparse Generalized Additive Models (Q5881076) (← links)
• (Q5886010) (← links)
• A fast unified algorithm for solving group-lasso penalize learning problems (Q5963816) (← links)
• SSGL (Q5984123) (← links)
• Sparse quadratic classification rules via linear dimension reduction (Q6032761) (← links)
• Solving constrained nonsmooth group sparse optimization via group Capped-\(\ell_1\) relaxation and group smoothing proximal gradient algorithm (Q6043130) (← links)
• Grouped variable selection with discrete optimization: computational and statistical perspectives (Q6046300) (← links)
• Bayesian group selection in logistic regression with application to MRI data analysis (Q6050939) (← links)
• Variable selection in nonlinear function‐on‐scalar regression (Q6079866) (← links)
• Prediction of sports injuries in football: a recurrent time-to-event approach using regularized Cox models (Q6107409) (← links)
• Forward selection for feature screening and structure identification in varying coefficient models (Q6133729) (← links)
• A convex-Nonconvex strategy for grouped variable selection (Q6144411) (← links)
• Variable selection for nonparametric additive Cox model with interval‐censored data (Q6149261) (← links)
• Model selection for inferring Gaussian graphical models (Q6204969) (← links)
• Estimation and variable selection for generalized functional partially varying coefficient hybrid models (Q6494432) (← links)
• On selection of semiparametric spatial regression models (Q6541496) (← links)
• Continuous exact relaxation and alternating proximal gradient algorithm for partial sparse and partial group sparse optimization problems (Q6569683) (← links)
• A generalized formulation for group selection via ADMM (Q6571367) (← links)
• Smoothing composite proximal gradient algorithm for sparse group Lasso problems with nonsmooth loss functions (Q6584749) (← links)
• Nonconvex fusion penalties for high-dimensional hierarchical categorical variables (Q6595312) (← links)
• Oracle inequalities for weighted group Lasso in high-dimensional Poisson regression model (Q6597414) (← links)
• Penalized integrative semiparametric interaction analysis for multiple genetic datasets (Q6624693) (← links)
• Interpretability of bi-level variable selection methods (Q6625441) (← links)
• Sparse group penalties for bi-level variable selection (Q6625465) (← links)
• Scalable algorithms for semiparametric accelerated failure time models in high dimensions (Q6626746) (← links)
• Structured sparse logistic regression with application to lung cancer prediction using breath volatile biomarkers (Q6627506) (← links)
• Generalized regression estimators with concave penalties and a comparison to lasso type estimators (Q6636373) (← links)
• Multivariate scalar on multidimensional distribution regression with application to modeling the association between physical activity and cognitive functions (Q6649371) (← links)