Department of Applied Mathematics & Physics, Kyoto University

Technical Report 2008-015 (November 26, 2008)

Convergence Properties of the Regularized Newton Method for the Unconstrained Nonconvex Optimization
by Kenji Ueda and Nobuo Yamashita

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The regularized Newton method (RNM) is one of the efficient solution methods for the unconstrained convex optimization. It is well-known that the RNM has good convergence properties as compared to the steepest descent method and the pure Newton