Shifted CholeskyQR for computing the QR factorization of ill-conditioned matrices
The Cholesky QR algorithm is an efficient communication-minimizing algorithm for computing the QR factorization of a tall-skinny matrix $X\in\mathbb{R}^{m\times n}$, where $m\gg n$. Unfortunately it is inherently unstable and often breaks down when the matrix is ill-conditioned. A recent work [Yamam...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Society for Industrial and Applied Mathematics
2020
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