Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning

Our lower bound analysis shows that the sample complexities of BSGD cannot be improved for general convex objectives and nonconvex objectives except for smooth nonconvex objectives with Lipschitz continuous gradient estimator.