Bounding the expected run-time of nonconvex optimization with early stopping

20 Feb 2020Thomas FlynnKwang Min YuAbid MalikNicolas D'ImperioShinjae Yoo

This work examines the convergence of stochastic gradient-based optimization algorithms that use early stopping based on a validation function. The form of early stopping we consider is that optimization terminates when the norm of the gradient of a validation function falls below a threshold... (read more)

PDF Abstract

Code


No code implementations yet. Submit your code now

Tasks


Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.