A Modified Regularized Newton Method for Unconstrained Nonconvex Optimization
نویسندگان
چکیده
In this paper, we present a modified regularized Newton method for the unconstrained nonconvex optimization by using trust region technique. We show that if the gradient and Hessian of the objective function are Lipschitz continuous, then the modified regularized Newton method (M-RNM) has a global convergence property. Numerical results show that the algorithm is very efficient.
منابع مشابه
An efficient improvement of the Newton method for solving nonconvex optimization problems
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