A new regularized Hessian-free Newton-type method for smooth convex optimization achieves global O(k^{-2}) convergence and local quadratic convergence in a variant, with practical speedups over prior methods.
A regularized newton method without line search for un- constrained optimization.Computational Optimization and Applications, 59(1):321–351, 2014
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A Regularized Hessian-Free Inexact Newton-Type Method with Global $\mathcal{O}(k^{-2})$ Convergence
A new regularized Hessian-free Newton-type method for smooth convex optimization achieves global O(k^{-2}) convergence and local quadratic convergence in a variant, with practical speedups over prior methods.