Escaping from saddle points on Riemannian manifolds

Finding the global minimum to Eq. (1) is in general NP-hard; our goal is to find an approximate second order stationary point with first order optimization methods. We are interested in first-order methods because they are extremely prevalent in machine learning, partly because computing Hessians is often too costly.