Event-chain algorithms: taming randomness in Monte Carlo methods through irreversibility, factorization and lifting

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• Michel Manon (Orange Lab)
• Tuesday 18 July 2017, 12:10-12:50
• Seminar Room 1, Newton Institute.

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SIN - Scalable inference; statistical, algorithmic, computational aspects

I will first present the irreversible and rejection-free Monte Carlo methods recently developed in Physics under the name Event-Chain. They have proven to produce clear acceleration over standard Monte Carlo methods, thanks to the reduction of their random-walk behavior. Their irreversible nature relies on three key ingredients: the factorized filter, the generalized lifting framework and the infinitesimal moves.  Then, I will focus on the new Forward Event-Chain version that allows to reduce the randomization needed for ergodicity, leading to a striking speed-up. Finally, I will explain how the factorized filter may be the key to subsampling in Monte Carlo methods.

This talk is part of the Isaac Newton Institute Seminar Series series.

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