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| Verfasst von: | AlShehri, Mohammed Abdul Rahman [VerfasserIn]  |
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| | Antil, Harbir [VerfasserIn] |
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| | Herberg, Evelyn Christin [VerfasserIn] |
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| | Kouri, Drew P. [VerfasserIn] |
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| Titel: | An inexact semismooth Newton method with application to adaptive randomized sketching for dynamic optimization |
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| Verf.angabe: | Mohammed Alshehri, Harbir Antil, Evelyn Herberg, Drew P. Kouri |
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| E-Jahr: | 2024 |
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| Jahr: | 1 January 2024 |
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| Umfang: | 21 S. |
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| Illustrationen: | Illustrationen |
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| Fussnoten: | Online verfügbar 18 October 2023, Version des Artikels 18 October 2023 ; Gesehen am 10.06.2024 |
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| Titel Quelle: | Enthalten in: Finite elements in analysis and design |
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| Ort Quelle: | Amsterdam : North-Holland, 1985 |
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| Jahr Quelle: | 2024 |
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| Band/Heft Quelle: | 228(2024) vom: Jan., Artikel-ID 104052, Seite 1-21 |
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| ISSN Quelle: | 0168-874X |
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| Abstract: | In many applications, one can only access the inexact gradients and inexact hessian times vector products. Thus it is essential to consider algorithms that can handle such inexact quantities with a guaranteed convergence to solution. An inexact adaptive and provably convergent semismooth Newton method is considered to solve constrained optimization problems. In particular, dynamic optimization problems, which are known to be highly expensive, are the focus. A memory efficient semismooth Newton algorithm is introduced for these problems. The source of efficiency and inexactness is the randomized matrix sketching. Applications to optimization problems constrained by partial differential equations are also considered. |
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| DOI: | doi:10.1016/j.finel.2023.104052 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Volltext: https://doi.org/10.1016/j.finel.2023.104052 |
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| | Volltext: https://www.sciencedirect.com/science/article/pii/S0168874X23001452 |
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| | DOI: https://doi.org/10.1016/j.finel.2023.104052 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | Adaptivity |
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| | Compression methods |
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| | Convergence analysis |
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| | Inexact gradient and Hessian |
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| | Measure control |
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| | Nonsmooth optimization |
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| | Randomized sketching |
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| | Semismooth Newton |
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| | Variational discretization |
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| K10plus-PPN: | 1890960837 |
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| Verknüpfungen: | → Zeitschrift |
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¬An¬ inexact semismooth Newton method with application to adaptive randomized sketching for dynamic optimization / AlShehri, Mohammed Abdul Rahman [VerfasserIn]; 1 January 2024 (Online-Ressource)
