ADMM_EN_SMW: ADMM on l1 regularized quadratic program

Description Usage Arguments Details Value See Also

Description

Applies Alternating Direction Method of Multipliers to the l1-regularized quadratic program

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

Usage

1
ADMM_EN_SMW(Ainv, V, R, d, x0, lam, mu, maxits, tol, quiet)

Arguments

Ainv

Diagonal of A^{-1} term in SMW formula, where A is an n by n positive definite coefficient matrix.

V

Matrix from SMW formula.

R

Upper triangular matrix in Cholesky decomposition of I + U*Ainv*V.

d

nx1 dimensional column vector.

lam

Regularization parameter for l1 penalty, must be greater than zero.

mu

Augmented Lagrangian penalty parameter, must be greater than zero.

maxits

Number of iterations to run

tol

Vector of stopping tolerances, first value is absolute, second is relative tolerance.

quiet

Logical controlling display of intermediate statistics.

alpha

Step length.

Details

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

Value

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

call

The matched call.

x

Found solution.

y

Dual solution.

z

Slack variables.

k

Number of iterations used.

See Also

Used by: SDAD and the SDADcv cross-validation version.


accSDA documentation built on May 2, 2019, 5:42 a.m.