Low-Rank/Sparse-Inverse Decomposition via Woodbury

Victor K. Fuentes () and Jon Lee ()
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Victor K. Fuentes: University of Michigan
Jon Lee: University of Michigan

A chapter in Operations Research Proceedings 2016, 2018, pp 111-117 from Springer

Abstract: Abstract Based on the Woodbury matrix identity, we present a heuristic and a test-problem generation method for decomposing an invertible input matrix into a low-rank component and a component having a sparse inverse.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-319-55702-1_16

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DOI: 10.1007/978-3-319-55702-1_16

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