On computing sparse universal solvers for key problems in statistics
Fuente:
arXiv
Salvato in:
| Autori principali: | , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866909770612473856 |
|---|---|
| author | Machado, Ananias Sousa Fampa, Marcia Lee, Jon |
| author_facet | Machado, Ananias Sousa Fampa, Marcia Lee, Jon |
| contents | We give sparsity results and present algorithms for calculating minimum (vector) 1-norm universal solvers connected to least-squares problems. In particular, besides universal least-squares solvers, we consider minimum-rank universal least-squares solvers, and simultaneous universal minimum-norm/least-squares solvers. For all of these, we present and compare several new alternative linear-optimization formulations and very effective proximal-point algorithms. Overall, we found that our new Douglas-Rachford splitting algorithms for these problems performed best. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_04264 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | On computing sparse universal solvers for key problems in statistics Machado, Ananias Sousa Fampa, Marcia Lee, Jon Optimization and Control We give sparsity results and present algorithms for calculating minimum (vector) 1-norm universal solvers connected to least-squares problems. In particular, besides universal least-squares solvers, we consider minimum-rank universal least-squares solvers, and simultaneous universal minimum-norm/least-squares solvers. For all of these, we present and compare several new alternative linear-optimization formulations and very effective proximal-point algorithms. Overall, we found that our new Douglas-Rachford splitting algorithms for these problems performed best. |
| title | On computing sparse universal solvers for key problems in statistics |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2509.04264 |