On the convergence of generalized kernel-based interpolation by greedy data selection algorithms
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866915031965237248 |
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| author | Albrecht, Kristof Iske, Armin |
| author_facet | Albrecht, Kristof Iske, Armin |
| contents | We analyze the convergence of generalized kernel-based interpolation methods. This is done under minimalistic assumptions on both the kernel and the target function. On these grounds, we further prove convergence of popular greedy data selection algorithms for totally bounded sets of sampling functionals. Supporting numerical results concerning computerized tomography are provided for illustration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_03840 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | On the convergence of generalized kernel-based interpolation by greedy data selection algorithms Albrecht, Kristof Iske, Armin Numerical Analysis We analyze the convergence of generalized kernel-based interpolation methods. This is done under minimalistic assumptions on both the kernel and the target function. On these grounds, we further prove convergence of popular greedy data selection algorithms for totally bounded sets of sampling functionals. Supporting numerical results concerning computerized tomography are provided for illustration. |
| title | On the convergence of generalized kernel-based interpolation by greedy data selection algorithms |
| topic | Numerical Analysis |
| url | https://arxiv.org/abs/2407.03840 |