On Superlinear Convergence of Infeasible Interior-Point Algorithms for Linearly Constrained Convex Programs

This note derives bounds on the length of the primal-dual affine scaling directions associated with a linearly constrained convex program satisfying the following conditions: 1) the problem has a solution satisfying strict complementarity, 2) the Hessian of the objective function satisfies a certain invariance property. We illustrate the usefulness of these bounds by establishing the superlinear convergence of the algorithm presented in Wright and Ralph [22] for solving the optimality conditions associated with a linearly constrained convex program satisfying the above conditions.