The paper introduces matrix-multiplication-based iterative refinement for diagonalizable non-Hermitian eigendecompositions that achieves quadratic residual reduction for simple eigenvalues and includes cluster stabilization.
Japan Journal of Industrial and Applied Mathematics35(3), 1007–1035 (2018)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
extension 1
citation-polarity summary
fields
math.NA 1years
2026 1verdicts
UNVERDICTED 1roles
extension 1polarities
extend 1representative citing papers
citing papers explorer
-
Iterative Refinement for Diagonalizable Non-Hermitian Eigendecompositions
The paper introduces matrix-multiplication-based iterative refinement for diagonalizable non-Hermitian eigendecompositions that achieves quadratic residual reduction for simple eigenvalues and includes cluster stabilization.