Pages that link to "Item:Q2905105"
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The following pages link to Standardization and the group lasso penalty (Q2905105):
Displaying 32 items.
- Flexible and Interpretable Models for Survival Data (Q144105) (← links)
- A Note on Coding and Standardization of Categorical Variables in (Sparse) Group Lasso Regression (Q146016) (← links)
- Inexact coordinate descent: complexity and preconditioning (Q306308) (← links)
- Discussion of ``Correlated variables in regression: clustering and sparse estimation'' (Q394081) (← links)
- Variable selection for general index models via sliced inverse regression (Q480962) (← links)
- Additive model selection (Q513754) (← links)
- Variable selection in multivariate linear models for functional data via sparse regularization (Q830251) (← links)
- Functional additive regression (Q888512) (← links)
- A flexible coordinate descent method (Q1639710) (← links)
- Simultaneous nonparametric regression in RADWT dictionaries (Q1727921) (← links)
- Penalized Cox's proportional hazards model for high-dimensional survival data with grouped predictors (Q2058906) (← links)
- On consistency and sparsity for high-dimensional functional time series with application to autoregressions (Q2108488) (← links)
- Finite sample theory for high-dimensional functional/scalar time series with applications (Q2136615) (← links)
- Nonlinear mixed-effects scalar-on-function models and variable selection (Q2302475) (← links)
- Graphical models for zero-inflated single cell gene expression (Q2318662) (← links)
- Dynamic network reconstruction from heterogeneous datasets (Q2662303) (← links)
- PUlasso: High-Dimensional Variable Selection With Presence-Only Data (Q3304856) (← links)
- A General Framework for Estimation and Inference From Clusters of Features (Q4690957) (← links)
- Bayesian variable selection and coefficient estimation in heteroscedastic linear regression model (Q5036373) (← links)
- Sparse group lasso for multiclass functional logistic regression models (Q5085971) (← links)
- A new Gibbs sampler for Bayesian lasso (Q5086323) (← links)
- Group SLOPE – Adaptive Selection of Groups of Predictors (Q5229924) (← 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)
- Sparse quadratic classification rules via linear dimension reduction (Q6032761) (← links)
- Pareto-efficient designs for multi- and mixed-level supersaturated designs (Q6494384) (← links)
- Low-rank tensor regression for selection of grouped variables (Q6596183) (← links)
- Data-adaptive additive modeling (Q6625660) (← links)
- Interaction screening for high-dimensional heterogeneous data via robust hybrid metrics (Q6628207) (← links)
- Partially linear monotone methods with automatic variable selection and monotonicity direction discovery (Q6629808) (← links)
- DDAC-SpAM: A Distributed Algorithm for Fitting High-dimensional Sparse Additive Models with Feature Division and Decorrelation (Q6631694) (← links)
- Potential application of elastic nets for shared polygenicity detection with adapted threshold selection (Q6636243) (← links)
