Randomized algorithms for generalized singular value decomposition with application to sensitivity analysis

@article{Saibaba2020RandomizedAF,
  title={Randomized algorithms for generalized singular value decomposition with application to sensitivity analysis},
  author={Arvind K. Saibaba and Joseph L. Hart and Bart G. van Bloemen Waanders},
  journal={Numerical Linear Algebra with Applications},
  year={2020},
  volume={28}
}
The generalized singular value decomposition (GSVD) is a valuable tool that has many applications in computational science. However, computing the GSVD for large‐scale problems is challenging. Motivated by applications in hyper‐differential sensitivity analysis (HDSA), we propose new randomized algorithms for computing the GSVD which use randomized subspace iteration and weighted QR factorization. Detailed error analysis is given which provides insight into the accuracy of the algorithms and… 
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14 Citations

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