We introduce meta-factorization, a theory that describes matrix decompositions as solutions of linear matrix equations: the projector and the reconstruction equation. Meta-factorization reconstructs known factorizations, reveals their internal structures, and allows for introducing modifications, as illustrated with SVD, QR, and UTV factorizations. The prospect of meta-factorization also provides insights into computational aspects of generalized matrix inverses and randomized linear algebra algorithms. The relations between the Moore-Penrose pseudoinverse, generalized Nystr"{o}m method, and the CUR decomposition are revealed here as an illustration. Finally, meta-factorization offers hints on the structure of new factorizations and provides the potential of creating them.
A theory of meta-factorization
Meta-factorization provides a framework for understanding and modifying matrix decompositions, offering insights into generalized matrix inverses and new factorization techniques.
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- 2021
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- arXiv 2021
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- 1
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- arxiv.org/abs/2111.14385ARXIV-DEFAULT
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