A Trust Region Method for Finding Second-Order Stationarity in Linearly Constrained Non-Convex Optimization
arXiv:1904.06784
Abstract
Motivated by TRACE algorithm [Curtis et al. 2017], we propose a trust region algorithm for finding second order stationary points of a linearly constrained non-convex optimization problem. We show the convergence of the proposed algorithm to (ε_g, ε_H)-second order stationary points in \widetilde{\mathcal{O}}(\max{ε_g^{-3/2}, ε_H^{-3}}) iterations. This iteration complexity is achieved for general linearly constrained optimization without cubic regularization of the objective function.