Pages that link to "Item:Q1023690"

The following pages link to Efficient methods for estimating constrained parameters with applications to regularized (Lasso) logistic regression (Q1023690):

Displaying 8 items.

• Accelerating the quadratic lower-bound algorithm via optimizing the shrinkage parameter (Q425379) (← links)
• Favorability functions based on kernel density estimation for logistic models: a case study (Q1023800) (← links)
• A novel variational Bayesian method for variable selection in logistic regression models (Q1727887) (← links)
• Two algorithms for fitting constrained marginal models (Q1800112) (← links)
• Double fused Lasso regularized regression with both matrix and vector valued predictors (Q2044365) (← links)
• Lasso logistic regression, GSoft and the cyclic coordinate descent algorithm: application to gene expression data (Q2254457) (← links)
• Estimation bounds and sharp oracle inequalities of regularized procedures with Lipschitz loss functions (Q2313281) (← links)
• Model selection and parameter estimation of a multinomial logistic regression model (Q5219998) (← links)