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SUMMARY:On the hypocoercivity of some PDMP-Monte Carlo algorithms - Christ
 ophe Andrieu\, University of Bristol
DTSTART:20190118T160000Z
DTEND:20190118T170000Z
UID:TALK115906@talks.cam.ac.uk
CONTACT:Dr Sergio Bacallado
DESCRIPTION:Monte Carlo methods based on Piecewise Deterministic Markov Pr
 ocesses (PDMP) have recently received some attention. In this talk we disc
 uss (exponential) convergence to equilibrium for a broad sub-class of PDMP
 -MC\, covering Randomized Hamiltonian Monte Carlo\, the Zig-Zag process an
 d the Bouncy Particle Sampler as particular cases\, establishing hypocoerc
 ivity under fairly weak conditions and explicit bounds on the spectral gap
  in terms of the parameters of the dynamics. This allows us\, for example\
 , to discuss dependence of this gap on the dimension of the problem for so
 me classes of target distributions.\n\narXiv:1808.08592\n\n(joint work wit
 h Alain Durmus\, Nikolas Nüsken\, Julien Roussel)
LOCATION:MR12
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