Anderson acceleration with adaptive relaxation for convergent fixed-point iterations
Fuente:
arXiv
Enregistré dans:
| Auteur principal: | |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866929479196082176 |
|---|---|
| author | Lepage-Saucier, Nicolas |
| author_facet | Lepage-Saucier, Nicolas |
| contents | Two adaptive relaxation strategies are proposed for Anderson acceleration. They are specifically designed for applications in which mappings converge to a fixed point. Their superiority over alternative Anderson acceleration is demonstrated for linear contraction mappings. Both strategies perform well in three nonlinear fixed-point applications that include partial differential equations and the EM algorithm. One strategy surpasses all other Anderson acceleration implementations tested in terms of computation time across various specifications, including composite Anderson acceleration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_16920 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Anderson acceleration with adaptive relaxation for convergent fixed-point iterations Lepage-Saucier, Nicolas Numerical Analysis Two adaptive relaxation strategies are proposed for Anderson acceleration. They are specifically designed for applications in which mappings converge to a fixed point. Their superiority over alternative Anderson acceleration is demonstrated for linear contraction mappings. Both strategies perform well in three nonlinear fixed-point applications that include partial differential equations and the EM algorithm. One strategy surpasses all other Anderson acceleration implementations tested in terms of computation time across various specifications, including composite Anderson acceleration. |
| title | Anderson acceleration with adaptive relaxation for convergent fixed-point iterations |
| topic | Numerical Analysis |
| url | https://arxiv.org/abs/2408.16920 |