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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Dades bibliogràfiques
Autor principal:	Goyens, F
Altres autors:	Cartis, C
Format:	Thesis
Idioma:	English
Publicat:	2021
Matèries:	Numerical analysis

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