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Nonlinear Conjugate Gradient Methods for Unconstrained Optimization - Springer Optimization and Its Applications Neculai Andrei 1st ed. 2020 edition
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Nonlinear Conjugate Gradient Methods for Unconstrained Optimization - Springer Optimization and Its Applications
Neculai Andrei
Two approaches are known for solving large-scale unconstrained optimization problems—the limited-memory quasi-Newton method (truncated Newton method) and the conjugate gradient method.
498 pages, 90 Illustrations, color; 3 Illustrations, black and white; XXVIII, 498 p. 93 illus., 90 i
| メディア | 書籍 Paperback Book (ソフトカバーで背表紙を接着した本) |
| リリース済み | 2021年6月24日 |
| ISBN13 | 9783030429522 |
| 出版社 | Springer Nature Switzerland AG |
| ページ数 | 498 |
| 寸法 | 150 × 220 × 10 mm · 730 g |
| 言語 | ドイツ語 |
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