Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian inference as iterated random functions with applications to
  sequential inference in graphical models   We propose a general formalism of iterated random functions with semigroup
property, under which exact and approximate Bayesian posterior updates can be
viewed as specific instances. A convergence theory for iterated random
functions is presented. As an application of the general theory we analyze
convergence behaviors of exact and approximate message-passing algorithms that
arise in a sequential change point detection problem formulated via a latent
variable directed graphical model. The sequential inference algorithm and its
supporting theory are illustrated by simulated examples.

5
The categories of this paper are: gr-qc
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
18
The categories of this paper are: econ