In this paper, the Hager and Zhang (HZ) conjugate gradient (CG) method and the modified HZ (MHZ) CG method are presented for large-scale nonsmooth convex minimization. Under some mild conditions, convergent results of the proposed methods are established. Numerical results show that the presented methods can be better efficiency for large-scale nonsmooth problems, and several problems are tested (with the maximum dimensions to 100,000 variables).
The Modified HZ Conjugate Gradient Algorithm for Large-Scale Nonsmooth Optimization.
改进的 HZ 共轭梯度算法用于大规模非光滑优化
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作者:Yuan Gonglin, Sheng Zhou, Liu Wenjie
| 期刊: | PLoS One | 影响因子: | 2.600 |
| 时间: | 2016 | 起止号: | 2016 Oct 25; 11(10):e0164289 |
| doi: | 10.1371/journal.pone.0164289 | ||
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