Publications [#361343] of Jianfeng Lu

Papers Published

1. Chen, Z; Li, Y; Lu, J, On the global convergence of randomized coordinate gradient descent for non-convex optimization (January, 2021)
   (last updated on 2024/04/23)

   Abstract:
   In this work, we analyze the global convergence property of coordinate gradient descent with random choice of coordinates and stepsizes for non-convex optimization problems. Under generic assumptions, we prove that the algorithm iterate will almost surely escape strict saddle points of the objective function. As a result, the algorithm is guaranteed to converge to local minima if all saddle points are strict. Our proof is based on viewing coordinate descent algorithm as a nonlinear random dynamical system and a quantitative finite block analysis of its linearization around saddle points.