Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization

For the proof, we develop 1) a new symmetrization technique to capture the magnitudes of the symmetry and asymmetry, and 2) a quantitative perturbation analysis to approximate matrix derivatives.