Consistency and fluctuations for stochastic gradient Langevin dynamics

Abstract

Applying standard Markov chain Monte Carlo (MCMC) algorithms to large data sets is computationally expensive. Both the calculation of the acceptance probability and the creation of informed proposals usually require an iteration through the whole data set. The …

Sebastian Vollmer

Professor for Applications of Machine Learning

My research interests lie at the interface of applied probability, statistical inference and machine learning.