Presents provably accurate compressive sensing algorithms for one-pass sparse approximation of top eigenvectors of huge approximately low-rank matrices with sublinear runtime.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.IT 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Fast One-Pass Sparse Approximation of the Top Eigenvectors of Huge Approximately Low-Rank Matrices? Yes, $MAM^*$!
Presents provably accurate compressive sensing algorithms for one-pass sparse approximation of top eigenvectors of huge approximately low-rank matrices with sublinear runtime.