Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee

This paper focuses on the high-dimensional sampling of log-concave distributions with composite structures: p (dx) exp( g(x) f(x))dx. We develop a double randomization technique, which leads to a fast underdamped Langevin algorithm with a dimension-independent convergence guarantee.