NANAFeb 25, 2013

Smoothed analysis of componentwise condition numbers for sparse matrices

arXiv:1302.60042 citationsh-index: 36
Originality Incremental advance
AI Analysis

Provides theoretical guarantees for numerical stability of sparse matrix computations, benefiting researchers and practitioners in numerical linear algebra.

The paper performs a smoothed analysis of componentwise condition numbers for determinant computation, matrix inversion, and linear equations solving for sparse n×n matrices, obtaining bounds of order O(log n) for the expectations of the logarithm of these condition numbers. This implies small bounds on the smoothed loss of accuracy for triangular linear systems.

We perform a smoothed analysis of the componentwise condition numbers for determinant computation, matrix inversion, and linear equations solving for sparse n times n matrices. The bounds we obtain for the ex- pectations of the logarithm of these condition numbers are, in all three cases, of the order O(log n). As a consequence, small bounds on the smoothed loss of accuracy for triangular linear systems follow.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes