Daniel Yiming Cao

Efficiently Escaping Saddle Points under Generalized Smoothness via Self-Bounding Regularity

We study the optimization of non-convex functions that are not necessarily smooth (gradient and/or Hessian are Lipschitz) using first order methods. Smoothness is a restrictive assumption in machine learning in both theory and practice, motivating significant recent work on finding first order stati…