Online Variational Filtering and Parameter Learning. (arXiv:2110.13549v2 [stat.ML] UPDATED)

Web: http://arxiv.org/abs/2110.13549

We present a variational method for online state estimation and parameter
learning in state-space models (SSMs), a ubiquitous class of latent variable
models for sequential data. As per standard batch variational techniques, we
use stochastic gradients to simultaneously optimize a lower bound on the log
evidence with respect to both model parameters and a variational approximation
of the states' posterior distribution. However, unlike existing approaches, our
method is able to operate in an entirely online manner, such that historic
observations …

arxiv filtering learning ml online