On choosing the mass matrix for Hamiltonian Monte Carlo

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• Tor Fjelde and Tim Hargreaves, University of Cambridge
• Wednesday 31 May 2023, 11:00-12:30
• Cambridge University Engineering Department, CBL Seminar room BE4-38..

If you have a question about this talk, please contact Isaac Reid.

Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.

In this talk will first go through the basics of Hamiltonian Monte Carlo (HMC), and then discuss some old and some recent developments in the field, with a particular focus on the role of the covariance matrix of the momentum distribution.

Potential reading: Neal, R. M. (2012). Mcmc Using Hamiltonian Dynamics. arXiv:1206.1901. http://arxiv.org/abs/1206.1901v1. Girolami, M., & Calderhead, B. (2011). Riemann manifold langevin and hamiltonian monte carlo methods. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 73(2), 123–214. Betancourt, M. J., & Girolami, M. (2013). Hamiltonian monte carlo for hierarchical models. arXiv:1312.0906. http://arxiv.org/abs/1312.0906v1. Langmore, I., Dikovsky, M., Geraedts, S., Norgaard, P., & Behren, R. V. (2019). A condition number for hamiltonian monte carlo. arXiv:1905.09813. http://arxiv.org/abs/1905.09813v3.

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

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