New subspace minimization conjugate gradient methods based on regularization model for unconstrained optimization
Abstract
In this paper, two new subspace minimization conjugate gradient methods based on p-regularization models are proposed, where a special scaled norm in p-regularization model is analyzed. Different choices of special scaled norm lead to different solutions to the p-regularized subproblem. Based on the analyses of the solutions in a two-dimensional subspace, we derive new directions satisfying the sufficient descent condition. With a modified...
Paper Details
Title
New subspace minimization conjugate gradient methods based on regularization model for unconstrained optimization
Published Date
Oct 28, 2020
Journal
Volume
87
Issue
4
Pages
1501 - 1534
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