Pages that link to "Item:Q2642739"

The following pages link to Piecewise linear regularized solution paths (Q2642739):

Displaying 47 items.

• Post-Pareto analysis and a new algorithm for the optimal parameter tuning of the elastic net (Q2278891) (← links)
• Novel harmonic regularization approach for variable selection in Cox's proportional hazards model (Q2330191) (← links)
• Piecewise linear solution paths with application to direct weight optimization (Q2377976) (← links)
• Solution path for quantile regression with epsilon-insensitive loss in a reproducing kernel Hilbert space (Q2405941) (← links)
• Forward and backward least angle regression for nonlinear system identification (Q2409414) (← links)
• Learning and estimation applications of an online homotopy algorithm for a generalization of the LASSO (Q2438036) (← links)
• Adaptive piecewise polynomial estimation via trend filtering (Q2448732) (← links)
• A sparse large margin semi-supervised learning method (Q2511744) (← links)
• On the structure of regularization paths for piecewise differentiable regularization terms (Q2689863) (← links)
• Generalized methods and solvers for noise removal from piecewise constant signals. I: Background theory (Q2889164) (← links)
• Generalized methods and solvers for noise removal from piecewise constant signals. II: New methods (Q2889165) (← links)
• Splines for financial volatility (Q2920261) (← links)
• A Note on Application of Nesterov’s Method in Solving Lasso-Type Problems (Q2943784) (← links)
• Inference of Genetic Networks from Time Course Expression Data Using Functional Regression with Lasso Penalty (Q3015888) (← links)
• An ordinary differential equation-based solution path algorithm (Q3021184) (← links)
• Efficient Global Approximation of Generalized Nonlinear ℓ₁-Regularized Solution Paths and Its Applications (Q3069888) (← links)
• Weak Convergence of the Regularization Path in Penalized M-Estimation (Q3103136) (← links)
• The Dantzig Selector in Cox's Proportional Hazards Model (Q3103139) (← links)
• Estimating spatial covariance using penalised likelihood with weighted<i>L</i>₁penalty (Q3182743) (← links)
• Algorithms for Fitting the Constrained Lasso (Q3391167) (← links)
• Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization (Q3391453) (← links)
• DASSO: Connections Between the Dantzig Selector and Lasso (Q3551034) (← links)
• On the optimality of averaging in distributed statistical learning (Q4606521) (← links)
• Approximate penalization path for smoothly clipped absolute deviation (Q4912042) (← links)
• Robust regression for highly corrupted response by shifting outliers (Q4971442) (← links)
• A Generic Path Algorithm for Regularized Statistical Estimation (Q4975409) (← links)
• Robust sparse regression by modeling noise as a mixture of gaussians (Q5036623) (← links)
• Structured sparse support vector machine with ordered features (Q5073382) (← links)
• (Q5159406) (← links)
• (Q5159420) (← links)
• Solution paths of variational regularization methods for inverse problems (Q5236689) (← links)
• Paths Following Algorithm for Penalized Logistic Regression Using SCAD and MCP (Q5415904) (← links)
• Simultaneous Regression Shrinkage, Variable Selection, and Supervised Clustering of Predictors with OSCAR (Q5450461) (← links)
• ``FISTA'' in Banach spaces with adaptive discretisations (Q6043131) (← links)
• Accelerate the warm-up stage in the Lasso computation via a homotopic approach (Q6115541) (← links)
• \(L_1\)-penalized fraud detection support vector machines (Q6134388) (← links)
• Regularization paths of \(L_1\)-penalized ROC curve-optimizing support vector machines (Q6541813) (← links)
• A confidence machine for sparse high-order interaction model (Q6548908) (← links)
• Path-following methods for maximum a posteriori estimators in Bayesian hierarchical models: how estimates depend on hyperparameters (Q6573010) (← links)
• Weight bound constraints in mean-variance models: a robust control theory foundation via machine learning (Q6592279) (← links)
• A survey of numerical algorithms that can solve the Lasso problems (Q6602016) (← links)
• Variable selection using \(L_q\) penalties (Q6604398) (← links)
• Variable selection using P-splines (Q6604438) (← links)
• Convex Bidirectional Large Margin Classifiers (Q6621634) (← links)
• Predictive signature development based on maximizing the area between receiver operating characteristic curves (Q6629365) (← links)
• Ranking Features to Promote Diversity: An Approach Based on Sparse Distance Correlation (Q6631078) (← links)
• Bootstrap estimation of the proportion of outliers in robust regression (Q6657838) (← links)