Low-rank tensor completion with fractal-inspired multi-scale energy regularization
Low-rank tensor completion has become a fundamental tool for recovering high-dimensional data from incomplete observations. However, conventional methods rely primarily on algebraic low-rank priors and do not explicitly regulate how signal energy is distributed across scales. This study introduces a...
Furkejuvvon:
| Váldodahkkit: | , , , |
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| Materiálatiipa: | Artigo |
| Giella: | Inglês |
| Almmustuhtton: |
Frontiers Media S.A.
2026-03-01
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| Ráidu: | Frontiers in Applied Mathematics and Statistics |
| Fáttát: | |
| Liŋkkat: | https://www.frontiersin.org/articles/10.3389/fams.2026.1809903/full |
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