Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/336854
Type: Artigo
Title: A Newton-like method with mixed factorizations and cubic regularization for unconstrained minimization
Author: Birgin, E. G.
Martinez, J. M.
Abstract: A Newton-like method for unconstrained minimization is introduced in the present work. While the computer work per iteration of the best-known implementations may need several factorizations or may use rather expensive matrix decompositions, the proposed method uses a single cheap factorization per iteration. Convergence and complexity and results, even in the case in which the subproblems' Hessians are far from being Hessians of the objective function, are presented. Moreover, when the Hessian is Lipschitz-continuous, the proposed method enjoys O(epsilon-3/2) evaluation complexity for first-order optimality and O(epsilon-3) for second-order optimality as other recently introduced Newton method for unconstrained optimization based on cubic regularization or special trust-region procedures. Fairly successful and fully reproducible numerical experiments are presented and the developed corresponding software is freely available
Subject: Método de Newton-Raphson
Fatoração (Matemática)
Country: Estados Unidos
Editor: Springer
Rights: Fechado
Identifier DOI: 10.1007/s10589-019-00089-7
Address: https://link.springer.com/article/10.1007%2Fs10589-019-00089-7
Date Issue: 2019
Appears in Collections:IMECC - Artigos e Outros Documentos

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