University of Cambridge > Talks.cam > Statistics > On the hypocoercivity of some PDMP-Monte Carlo algorithms

  Browse A-Z

Log in

Googledetails Microsoftdetails

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹ️ Information

On the hypocoercivity of some PDMP-Monte Carlo algorithms

Download to your calendar using vCal

  • UserChristophe Andrieu, University of Bristol
  • ClockFriday 18 January 2019, 16:00-17:00
  • HouseMR12.

If you have a question about this talk, please contact Dr Sergio Bacallado .

Monte Carlo methods based on Piecewise Deterministic Markov Processes (PDMP) have recently received some attention. In this talk we discuss (exponential) convergence to equilibrium for a broad sub-class of PDMP -MC, covering Randomized Hamiltonian Monte Carlo, the Zig-Zag process and the Bouncy Particle Sampler as particular cases, establishing hypocoercivity 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 some classes of target distributions.

arXiv:1808.08592

(joint work with Alain Durmus, Nikolas Nüsken, Julien Roussel)

This talk is part of the Statistics series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

Zoom - link to be announced Biophysical Techniques Lecture Series 2017 Meeting Room 5, CMS

Other talks

Rothschild Public Lecture: The Quantum Centenary: from Order to Chaos From lab to clinic: an introduction to translational research Title to be confirmed Summer Cactus & Succulent Show Seminars in Cancer Group Work
 

© 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity