A Riemannian perspective on matrix recovery and constrained optimization

A Riemannian perspective on matrix recovery and constrained optimization

<p>Nonlinear matrix recovery is an emerging paradigm in which specific classes of high-rank matrices can be recovered from an underdetermined linear system of measurements. In particular, we consider matrices whose columns, seen as data points, belong to an algebraic variety, namely, a set def...

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Dettagli Bibliografici
Autore principale:	Goyens, F
Altri autori:	Cartis, C
Natura:	Tesi
Lingua:	English
Pubblicazione:	2021
Soggetti:	Numerical analysis

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