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- W2393371034 abstract "The super-memory gradient method has played a special role for solving large-scale unconstrained optimization problems due to its simplicity and the very low storage.In this paper,by combining the diagonal-sparse quasi-Newton technique with the modified Gu and Mo non-monotone line search method,a new super-memory gradient method for unconstrained optimization problems is presented.The global convergence property of the new method is analyzed.The new method has two properties: it converges stably and can solve ill-conditioned problems,it only needs simple computation so as to solve large-scale problems.The numerical results show that the new method is effective and stable in practical computation." @default.
- W2393371034 created "2016-06-24" @default.
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- W2393371034 date "2012-01-01" @default.
- W2393371034 modified "2023-09-26" @default.
- W2393371034 title "A Non-monotone Super-memory Gradient Method Based on the Diagonal-sparse Quasi-Newton Direction" @default.
- W2393371034 hasPublicationYear "2012" @default.
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