Read Between the Hyperplanes: On Spectral Projection and Sampling Approaches to Randomized Kaczmarz
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866914358148202496 |
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| author | Nguyen, James Presnyakov, Oleg Radhakhrishnan, Adityakrishnan |
| author_facet | Nguyen, James Presnyakov, Oleg Radhakhrishnan, Adityakrishnan |
| contents | Among recent developments centered around Randomized Kaczmarz (RK), a row-sampling iterative projection method for large-scale linear systems, several adaptions to the method have inspired faster convergence. Focusing solely on ill-conditioned and overdetermined linear systems, we highlight inter-row relationships that can be leveraged to guide directionally aware projections. In particular, we find that improved convergence rates can be made by (i) projecting onto pairwise row differences, (ii) sampling from partitioned clusters of nearly orthogonal rows, or (iii) more frequently sampling spectrally-diverse rows. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_03055 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Read Between the Hyperplanes: On Spectral Projection and Sampling Approaches to Randomized Kaczmarz Nguyen, James Presnyakov, Oleg Radhakhrishnan, Adityakrishnan Numerical Analysis 65B99, 65F10, 65F20 Among recent developments centered around Randomized Kaczmarz (RK), a row-sampling iterative projection method for large-scale linear systems, several adaptions to the method have inspired faster convergence. Focusing solely on ill-conditioned and overdetermined linear systems, we highlight inter-row relationships that can be leveraged to guide directionally aware projections. In particular, we find that improved convergence rates can be made by (i) projecting onto pairwise row differences, (ii) sampling from partitioned clusters of nearly orthogonal rows, or (iii) more frequently sampling spectrally-diverse rows. |
| title | Read Between the Hyperplanes: On Spectral Projection and Sampling Approaches to Randomized Kaczmarz |
| topic | Numerical Analysis 65B99, 65F10, 65F20 |
| url | https://arxiv.org/abs/2511.03055 |