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Extended ensemble Monte Carlo

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If you have a question about this talk, please contact Konstantina Palla.

This RCC will review a family of MCMC sampling procedures that can improve on standard methods by a somewhat counterintuitive trick: enhancing the state space by some auxiliary variables and doing sampling in this extended space. In particular, we will cover several methods related to annealing, in which the auxiliary variable takes the form of temperature, but also some problem-specific examples, such as the Swendsen-Wang algorithm for sampling from Potts models, or the estimation of partition function ratios by sampling.

The RCC will be tutorial in nature and thus there is no required reading.

This talk is part of the Machine Learning Reading Group @ CUED series.

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