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...
| Autor Principal: | |
|---|---|
| Outros autores: | |
| Formato: | Thesis |
| Idioma: | English |
| Publicado: |
2021
|
| Subjects: |