Stochastic Compositional Optimization via Hybrid Momentum Frank--Wolfe
The Hybrid Momentum Stochastic Frank–Wolfe algorithm solves optimization problems where an outer function F is not continuously differentiable, which excludes many practical applications like CVaR. It introduces a novel stochastic projection-free method that maintains two trackers to handle non-smoothness in the outer function, achieving optimal convergence rates of O(K^-1/4) for non-convex objectives.