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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Détails bibliographiques
Auteur principal: Goyens, F
Autres auteurs: Cartis, C
Format: Thèse
Langue:English
Publié: 2021
Sujets:

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