Abstract: Training machine learning models often involves solving high-dimensional stochastic optimization problems, where stochastic gradient-based algorithms are hindered by slow convergence.

Abstract: Recent advances in diffusion models (DMs)—such as few-step denoising and multi-modal conditioning—have significantly improved computational efficiency and functional flexibility, but they ...