prox_EN: Accelerated Proximal Gradient on l1 regularized quadratic...

In accSDA: Accelerated Sparse Discriminant Analysis

Accelerated Proximal Gradient on l1 regularized quadratic program

Description

Applies accelerated proximal gradient algorithm to the l1-regularized quadratic program

f(x) + g(x) = 0.5*x^T*A*x - d^T*x + lambda*|x|_l1

Usage

prox_EN(A, d, x0, lam, alpha, maxits, tol)

Arguments

A	p by p positive definite coefficient matrix A = (gamma Om + X^T X/n) .
d	nx1 dimensional column vector.
lam	Regularization parameter for l1 penalty, must be greater than zero.
alpha	Step length.
maxits	Number of iterations to run
tol	Stopping tolerance for proximal gradient algorithm.

Details

This function is used by other functions and should only be called explicitly for debugging purposes.

Value

prox_EN returns an object of class "prox_EN" including a list with the following named components

call

The matched call.

x

Found solution.

k

Number of iterations used.

See Also

Used by: SDAP and the SDAPcv cross-validation version.

accSDA documentation built on Sept. 5, 2022, 5:05 p.m.