backtrack               Backtracking Line Search
ddg                     Compute the approximate Hessian of the
                        majorization.
dg                      Compute the gradient of the majorization.
mmqn_step               MM-quasi-Newton step
nmsfp_mm                MM algorithm for nonlinear multiple-sets split
                        feasibility problem
nmsfp_mmqn              MM algorithm (accelerated) for nonlinear
                        multiple-sets split feasibility problem
nmsfp_sap               Self-adaptive projection-type method algorithm
                        for nonlinear multiple-sets split feasibility
                        problem
nmsfp_sap_one_step      One step of self-adaptive projection-type
                        method for the NMSFP
project_ball            Projection onto a ball
project_cube            Project onto a cube
project_halfspace       Projection onto a halfspace
project_square          Project onto a square
proximity               Proximity function
qnamm                   Quasi-Newton acceleration of MM algorithm
softmax                 Compute soft-max
split_feasibility       split_feasibility
wood_inv_solve          Compute the inverse approximate Hessian of the
                        majorization using the Woodbury inversion
                        formula. 'wood_inv_solve' computes the inverse
                        of the Hessian term of the majorization of the
                        proximity function using the Woodbury formula.
                        The function 'mmqn_step' invokes
                        'wood_inv_solve' instead of ddg if the argument
                        'woodbury=TRUE'. This should be used when p <<
                        n.
