Pages that link to "Item:Q2482976"

The following pages link to Coordinate descent algorithms for lasso penalized regression (Q2482976):

Displaying 50 items.

• Standardization and the group lasso penalty (Q2905105) (← links)
• Estimation for high-dimensional linear mixed-effects models using \(\ell_1\)-penalization (Q2911662) (← links)
• Laplace Error Penalty-based Variable Selection in High Dimension (Q2949868) (← links)
• A Penalized Likelihood Approach for Bivariate Conditional Normal Models for Dynamic Co-expression Analysis (Q3008891) (← links)
• Penalized and Constrained Optimization: An Application to High-Dimensional Website Advertising (Q3304839) (← links)
• PUlasso: High-Dimensional Variable Selection With Presence-Only Data (Q3304856) (← links)
• Regularized Estimation and Feature Selection in Mixtures of Gaussian-Gated Experts Models (Q3305484) (← links)
• Coordinate majorization descent algorithm for nonconvex penalized regression (Q3389674) (← links)
• A fast algorithm for the accelerated failure time model with high-dimensional time-to-event data (Q3390327) (← links)
• Accelerated, Parallel, and Proximal Coordinate Descent (Q3449571) (← links)
• An Accelerated Randomized Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization (Q3451763) (← links)
• Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure (Q3459931) (← links)
• Group variable selection via convex log‐exp‐sum penalty with application to a breast cancer survivor study (Q3465722) (← links)
• (Q4558147) (← links)
• Adaptive Randomized Coordinate Descent for Sparse Systems: Lasso and Greedy Algorithms (Q4580720) (← links)
• A Randomized Nonmonotone Block Proximal Gradient Method for a Class of Structured Nonlinear Programming (Q4596724) (← links)
• On the complexity of parallel coordinate descent (Q4638927) (← links)
• Applications of L1 regularisation (Q4639259) (← links)
• Functional logistic regression: a comparison of three methods (Q4960543) (← links)
• Model Selection for High-Dimensional Quadratic Regression via Regularization (Q4962427) (← links)
• Maximum Likelihood Estimation Over Directed Acyclic Gaussian Graphs (Q4969868) (← links)
• Hierarchical models for multiple, rare outcomes using massive observational healthcare databases (Q4970199) (← links)
• Conducting sparse feature selection on arbitrarily long phrases in text corpora with a focus on interpretability (Q4970223) (← links)
• Robust regression for highly corrupted response by shifting outliers (Q4971442) (← links)
• (Q4999080) (← links)
• A descent algorithm for constrained LAD-Lasso estimation with applications in portfolio selection (Q5034163) (← links)
• An empirical threshold of selection probability for analysis of high-dimensional correlated data (Q5036882) (← links)
• Hierarchical Total Variations and Doubly Penalized ANOVA Modeling for Multivariate Nonparametric Regression (Q5066471) (← links)
• A proximal dual semismooth Newton method for zero-norm penalized quantile regression estimator (Q5066792) (← links)
• Sparsely restricted penalized estimators (Q5078476) (← links)
• Review of Bayesian selection methods for categorical predictors using JAGS (Q5093004) (← links)
• Sparse alternatives to ridge regression: a random effects approach (Q5130118) (← links)
• Confidence Intervals for Sparse Penalized Regression With Random Designs (Q5130623) (← links)
• (Q5134850) (← links)
• The sliding Frank–Wolfe algorithm and its application to super-resolution microscopy (Q5210421) (← links)
• A coordinate majorization descent algorithm for ℓ₁penalized learning (Q5219208) (← links)
• Nested coordinate descent algorithms for empirical likelihood (Q5219446) (← links)
• Model-averaged ℓ₁regularization using Markov chain Monte Carlo model composition (Q5220776) (← links)
• Exponential regression for censored data with outliers (Q5222343) (← links)
• <b><tt>cmenet</tt></b>: A New Method for Bi-Level Variable Selection of Conditional Main Effects (Q5231511) (← links)
• Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion (Q5251927) (← links)
• Convex biclustering (Q5347398) (← links)
• Multiple Self‐Controlled Case Series for Large‐Scale Longitudinal Observational Databases (Q5408010) (← links)
• Lasso Regression: Estimation and Shrinkage via the Limit of Gibbs Sampling (Q5743229) (← links)
• Mixed Lasso estimator for stochastic restricted regression models (Q5861222) (← links)
• Prediction of tumour pathological subtype from genomic profile using sparse logistic regression with random effects (Q5861537) (← links)
• Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors (Q5962732) (← links)
• A fast unified algorithm for solving group-lasso penalize learning problems (Q5963816) (← links)
• Structured sparsity through convex optimization (Q5965303) (← links)
• A selective review of group selection in high-dimensional models (Q5965305) (← links)