Construct · 1 fields · 1 citations

robust principal component analysis: a standalone construct

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Signal processing

recovery of a low-rank matrix and a sparse corruption matrix from their sum by convex optimization, separating background structure from gross errors.

In signal processing, robust principal component analysis refers to recovery of a low-rank matrix and a sparse corruption matrix from their sum by convex optimization, separating background structure from gross errors. This meaning comes from Candès (2011) in Journal of the ACM.[1]

Unit
Recovery means
Measured by

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Nearby constructs

component analysis1 fields · 1 citationsanchor · a standalone construct component3 fields · 5 citationsjingle · one word, three constructs matrix3 fields · 4 citationsjingle · one word, three constructs

References

Candès, E. J., Li, X., Ma, Y., & Wright, J. (2011). Robust principal component analysis? Journal of the ACM, 58(3), 1-37. https://doi.org/10.1145/1970392.1970395

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