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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

29 September 2022
Yuetian Luo
Nicolas García Trillos
ArXivPDFHTML

Papers citing "Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape Analysis for Fixed-rank Matrix Optimization From a Riemannian Perspective"

4 / 4 papers shown
Title
Low solution rank of the matrix LASSO under RIP with consequences for
  rank-constrained algorithms
Low solution rank of the matrix LASSO under RIP with consequences for rank-constrained algorithms
Andrew D. McRae
35
1
0
19 Apr 2024
Spectral Neural Networks: Approximation Theory and Optimization
  Landscape
Spectral Neural Networks: Approximation Theory and Optimization Landscape
Chenghui Li
Rishi Sonthalia
Nicolas García Trillos
24
1
0
01 Oct 2023
Invex Programs: First Order Algorithms and Their Convergence
Invex Programs: First Order Algorithms and Their Convergence
Adarsh Barik
S. Sra
Jean Honorio
8
2
0
10 Jul 2023
Forward-backward Gaussian variational inference via JKO in the
  Bures-Wasserstein Space
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space
Michael Diao
Krishnakumar Balasubramanian
Sinho Chewi
Adil Salim
BDL
13
20
0
10 Apr 2023
1