Abstract: The stochastic subgradient method is a widely used algorithm for solving large-scale optimization problems arising in machine learning. Often, these problems are neither smooth nor convex.
Abstract: This study presents and examines a randomized incremental subgradient algorithm designed to tackle convex optimization problems on Riemannian manifolds. The objective function comprises ...