wood_inv_solve

weights for first set of constraints

weights for second set of constraints

Handle for output mapping Jacobian

hgrad

Compute the inverse approximate Hessian of the majorization using the Woodbury inversion formula.
<code>wood_inv_solve</code> computes the inverse of the Hessian term of the majorization of the proximity function
using the Woodbury formula. The function <code>mmqn_step</code> invokes <code>wood_inv_solve</code> instead of ddg if the argument
<code>woodbury=TRUE</code>. This should be used when p &lt;&lt; n.

An implementation of the majorization-minimization (MM) algorithm introduced by
Xu, Chi, Yang, and Lange (2017) <arXiv:1612.05614> for solving multi-set split feasibility problems. In the multi-set split feasibility problem, we seek to find a point x
in the intersection of multiple closed sets and whose image under a mapping also must fall in the intersection of several closed sets.

Eric Chi

splitFeas

Multi-Set Split Feasibility

Jason Xu

Meng Yang

Kenneth Lange

wood_inv_solve function

Compute the inverse approximate Hessian of the majorization using the Woodbury inversion formula.
<code>wood_inv_solve</code> computes the inverse of the Hessian term of the majorization of the proximity function
using the Woodbury formula. The function <code>mmqn_step</code> invokes <code>wood_inv_solve</code> instead of ddg if the argument
<code>woodbury=TRUE</code>. This should be used when p &lt;&lt; n. — wood_inv_solve

Compute the inverse approximate Hessian of the majorization using the Woodbury inversion formula.
<code>wood_inv_solve</code> computes the inverse of the Hessian term of the majorization of the proximity function
using the Woodbury formula. The function <code>mmqn_step</code> invokes <code>wood_inv_solve</code> instead of ddg if the argument
<code>woodbury=TRUE</code>. This should be used when p &lt;&lt; n.

Description

Usage

Arguments