7th February 2005 — Annealing Review

Iain and David will review annealing methods, focussing on Bayesian uses.

Please take a look at sections 6.1 and 6.2 of Probabilistic Inference Using Markov Chain Monte Carlo Methods, Radford M. Neal, 1993.

If you are unfamiliar with normal MCMC methods, such as the Metropolis algorithm, read up on that instead as it will not be reviewed. Try either the review above or David’s book.

For reference the papers Iain used were:

Particularly recommended is “Tempered transitions” for its discussion.

“Regeneration” has been applied to simulated tempering and multicanonical ensemble methods. Perhaps allows “pre-simulation” for weights to be a bit less wasteful. I’m afraid you’ll have to chase the references yourself. Naively it is probably fairly easy to apply.

Also recommended is the following review paper shown to him afterwards:

And this oft-cited paper:

Note that we did not cover the neat methods in BayeSys or Nested Sampling, acceptance ratio methods (as such), Hamiltonian Monte Carlo (as found in fbm), Dragging fast variables, a bunch of classical techniques, some newer variations of the above methods, or probably a zillion other annealing-related ideas.