something like Pauly D over epsilon four or something okay so gradient descent I'm very very very over parameterize networks converges to global minimizer's so over parameterization does help even when you have regularization the mechanism in which it helps is very different from this local convex intuition the intuition here is that when you're very very over primate rising there's a descent direction in function space but if you have a finite a small width network you might miss the function space because you might miss