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...

書誌詳細
第一著者:	Goyens, F
その他の著者:	Cartis, C
フォーマット:	学位論文
言語:	English
出版事項:	2021
主題:	Numerical analysis

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