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Titlebook: Numerical Optimization with Computational Errors; Alexander J. Zaslavski Book 2016 Springer International Publishing Switzerland 2016 nonl

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21#
發(fā)表于 2025-3-25 07:00:15 | 只看該作者
22#
發(fā)表于 2025-3-25 10:08:04 | 只看該作者
23#
發(fā)表于 2025-3-25 12:16:53 | 只看該作者
24#
發(fā)表于 2025-3-25 17:15:49 | 只看該作者
25#
發(fā)表于 2025-3-25 22:30:39 | 只看該作者
26#
發(fā)表于 2025-3-26 01:57:04 | 只看該作者
Proximal Point Method in Hilbert Spaces,how the convergence of proximal point methods when computational errors are summable. In this chapter the convergence of the method is established for nonsummable computational errors. We show that the proximal point method generates a good approximate solution if the sequence of computational errors is bounded from above by some constant.
27#
發(fā)表于 2025-3-26 04:35:17 | 只看該作者
28#
發(fā)表于 2025-3-26 10:36:31 | 只看該作者
Maximal Monotone Operators and the Proximal Point Algorithm,one operator, under the presence of computational errors. The convergence of the method is established for nonsummable computational errors. We show that the proximal point method generates a good approximate solution, if the sequence of computational errors is bounded from above by a constant.
29#
發(fā)表于 2025-3-26 13:46:56 | 只看該作者
The Extragradient Method for Solving Variational Inequalities,errors. The convergence of the subgradient method for solving variational inequalities is established for nonsummable computational errors. We show that the subgradient method generates a good approximate solution, if the sequence of computational errors is bounded from above by a constant.
30#
發(fā)表于 2025-3-26 18:54:12 | 只看該作者
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