Mohammad Mahdi Ahmadi

Stochastic Dynamic Barrier Perturbed Gradient Methods for Nonconvex Simple Bilevel Optimization

PR-SDBPG, a penalty-regularized variant that eliminates the rare-visit assumption, and VR-PR-SDBPG, which improves the resulting sample complexities entirely through variance reduction, are developed, believed to be the first explicit stochastic nonconvex-nonconvex simple bilevel optimization guarantees.