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...
主要作者: | Goyens, F |
---|---|
其他作者: | Cartis, C |
格式: | Thesis |
语言: | English |
出版: |
2021
|
主题: |
相似书籍
-
Nonlinear matrix recovery using optimization on the Grassmann manifold
由: Goyens, F, et al.
出版: (2022) -
Control perspectives on numerical algorithms and matrix problems /
由: 444990 Bhaya, Amit, et al.
出版: (2006) -
Basis set approach in the constrained interpolation profile method /
由: Utsumi, T., et al.
出版: (2003) -
Fast iterative solvers for PDE-constrained optimization problems
由: Pearson, J
出版: (2013) -
Efficient algorithms for compressed sensing and matrix completion
由: Wei, K
出版: (2014)