Block Low-Rank Matrices with Shared Bases: Potential and Limitations of the BLR^2 Format

Autor: Alfredo Buttari, Théo Mary, Cleve Ashcraft

Publikováno v: SIAM Journal on Matrix Analysis and Applications
SIAM Journal on Matrix Analysis and Applications, Society for Industrial and Applied Mathematics, In press

International audience; We investigate a special class of data sparse rank-structured matrices that combine a flat block low-rank (BLR) partitioning with the use of shared (called nested in the hierarchical case) bases. This format is to H 2 matrices

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fecb1ae5c38c8f29d9e1f7789ab3f8c4
https://hal.archives-ouvertes.fr/hal-03070416/file/paper.pdf