Inexact regularized Newton method for unconstrained optimization with rapid rate of convergence
This paper proposes an inexact regularized Newton method for solving unconstrained optimization
problems. The proposed algorithm belongs to the class of outer-inner iteration scheme. Instead of solving
exactly linear systems, iterative linear solver will be applied to find approximate search directions. We will
show that the inexact algorithm preserved the fast local convergence property of exact algorithms. Some
numerical experiments are also conducted to show the benefits of our proposed algorithm.