Random orthonormal matrices are minimax optimal for sketched least squares and rotation-invariant embeddings for randomized SVD, yielding the sharpest error bounds.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.NA 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Sharp analysis of sketched least squares and randomized low-rank approximation
Random orthonormal matrices are minimax optimal for sketched least squares and rotation-invariant embeddings for randomized SVD, yielding the sharpest error bounds.