Mild logarithmic overparametrization in Burer-Monteiro nonconvex optimization yields optimal sample complexity and error for phase retrieval and rank-1 matrix sensing via a new semidefinite-structure analysis of second-order critical points.
Preconditioned gradient descent for overparameterized nonconvex Burer–Monteiro factorization with global optimality certification,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Phase retrieval and matrix sensing via benign and overparametrized nonconvex optimization
Mild logarithmic overparametrization in Burer-Monteiro nonconvex optimization yields optimal sample complexity and error for phase retrieval and rank-1 matrix sensing via a new semidefinite-structure analysis of second-order critical points.