A simple filter for detecting low-rank submatrices
From MaRDI portal
Publication:419636
DOI10.1016/j.jcp.2011.12.032zbMath1242.65082OpenAlexW2043905333MaRDI QIDQ419636
Publication date: 18 May 2012
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jcp.2011.12.032
algorithmdata analysisrandom projectionmatrix compressionbiclusteringdetecting low-rank submatriceeccentric Gaussian distributions
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Cites Work
- Unnamed Item
- Detecting low-rank clusters via random sampling
- Efficient methods for grouping vectors into low-rank clusters
- A randomized algorithm for the decomposition of matrices
- A fast randomized algorithm for the approximation of matrices
- Using underapproximations for sparse nonnegative matrix factorization
- The maximum edge biclique problem is NP-complete
- Randomized algorithms for the low-rank approximation of matrices
- A Fast $ULV$ Decomposition Solver for Hierarchically Semiseparable Representations
- A Fast Solver for HSS Representations via Sparse Matrices
This page was built for publication: A simple filter for detecting low-rank submatrices
