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On Geometric Connections of Embedded and Quotient Geometries in
  Riemannian Fixed-rank Matrix Optimization
v1v2 (latest)

On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-rank Matrix Optimization

Mathematics of Operations Research (MOR), 2021
23 October 2021
Yuetian Luo
Xudong Li
Xinmiao Zhang
ArXiv (abs)PDFHTML

Papers citing "On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-rank Matrix Optimization"

3 / 3 papers shown
Spectral Neural Networks: Approximation Theory and Optimization
  Landscape
Spectral Neural Networks: Approximation Theory and Optimization Landscape
Chenghui Li
Rishi Sonthalia
Nicolas García Trillos
240
2
0
01 Oct 2023
Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape
  Analysis for Fixed-rank Matrix Optimization From a Riemannian Perspective
Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape Analysis for Fixed-rank Matrix Optimization From a Riemannian Perspective
Yuetian Luo
Nicolas García Trillos
231
8
0
29 Sep 2022
Nonconvex Factorization and Manifold Formulations are Almost Equivalent
  in Low-rank Matrix Optimization
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization
Yuetian Luo
Xudong Li
Anru R. Zhang
291
11
0
03 Aug 2021
1