Michael I. Jordan
University of California, Berkeley
June 11, 2020
Langevin diffusions are continuous-time stochastic processes that are based on the gradient of a potential function. As such they have many connections---some known and many still to be explored---to gradient-based machine learning. I'll discuss several recent results in this vein: (1) the use of Langevin-based algorithms in bandit problems; (2) the acceleration of Langevin diffusions; (3) how to use Langevin Monte Carlo without making smoothness assumptions.