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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
| Médias | Livres Paperback Book (Livre avec couverture souple et dos collé) |
| Validé | 24 juin 2021 |
| ISBN13 | 9783030429522 |
| Éditeurs | Springer Nature Switzerland AG |
| Pages | 498 |
| Dimensions | 234 × 155 × 30 mm · 790 g |
| Langue et grammaire | Allemand |
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