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multicanonical sampling

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If you have a question about this talk, please contact David MacKay.

In multicanonical ensemble and other artificial ensemble Monte Carlo methods one samples from from a distribution different than the canonical (the true posterior distribution) in order to make the relaxation of the Markov chain more effective. I will lead a discussion of some of these techniques and try to indicate that they actually involve inference problems.

The presentation will be based upon the review in Jesper Ferkinghoff-Borg’s thesis, available from http://www.nbi.dk/~borg/

This talk is part of the Machine Learning Journal Club series.

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