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Titlebook: Numerical Optimization; Theoretical and Prac J. Frédéric Bonnans,J. Charles Gilbert,Claudia A. Textbook 20031st edition Springer-Verlag Be

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31#
發(fā)表于 2025-3-26 21:50:21 | 只看該作者
32#
發(fā)表于 2025-3-27 04:20:11 | 只看該作者
J. Frédéric Bonnans,J. Charles Gilbert,Claudia A. Combines mathematical developments, description and analysis of algorithms.Selection of algorithms is based on their applicability to real-life problems.Includes supplementary material:
33#
發(fā)表于 2025-3-27 06:17:15 | 只看該作者
General Introductiont will be the usual dot-product: .); | · | or ∥ · ∥ will denote the associated norm. The . (vector of partial derivatives) of a function .: ?. → ? will be denoted by ? . or .′; the . (matrix of second derivatives) by ?.. or .″. We will also use continually the notation .(.) = .′(.).
34#
發(fā)表于 2025-3-27 09:42:35 | 只看該作者
Special Methodsmely important, and might supersede line-searches, sooner or later. The other methods deal with the direction; they are either classical (Gauss-Newton) or recent (limited-memory quasi-Newton, truncated Newton) and apply only in some well-defined subclasses of problems.
35#
發(fā)表于 2025-3-27 17:07:25 | 只看該作者
36#
發(fā)表于 2025-3-27 19:44:26 | 只看該作者
37#
發(fā)表于 2025-3-28 00:39:31 | 只看該作者
38#
發(fā)表于 2025-3-28 05:33:06 | 只看該作者
39#
發(fā)表于 2025-3-28 07:18:26 | 只看該作者
Bundle Methods. The Quest of DescentNone of the black-box methods considered so far are descent schemes. Only the steepest-descent method guarantees a decrease of the objective function at each iteration. However, it requires the complete knowledge of .., and can be unstable.
40#
發(fā)表于 2025-3-28 10:41:57 | 只看該作者
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