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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| フォーマット: | 学位論文 |
| 言語: | English |
| 出版事項: |
2021
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