Stochastic Approximation with Biased MCMC for Expectation Maximization

arXiv:2402.17870v1 Announce Type: cross
Abstract: The expectation maximization (EM) algorithm is a widespread method for empirical Bayesian inference, but its expectation step (E-step) is often intractable. Employing a stochastic approximation scheme with Markov chain Monte Carlo (MCMC) can circumvent this issue, resulting in an algorithm known as MCMC-SAEM. While theoretical guarantees for MCMC-SAEM have previously been established, these results are restricted to the case where asymptotically unbiased MCMC algorithms are used. In practice, MCMC-SAEM is often run with asymptotically biased …

abstract algorithm approximation arxiv bayesian bayesian inference cs.lg inference issue markov math.oc mcmc stat.co stat.ml stochastic type