Kinetic energy choice in Hamiltonian/hybrid Monte Carlo
- đ¤ Speaker: Sam Livingstone (University of Bristol)
- đ Date & Time: Wednesday 05 July 2017, 11:00 - 11:45
- đ Venue: Seminar Room 1, Newton Institute
Abstract
We consider how different choices of kinetic energy in Hamiltonian Monte Carlo affect algorithm performance. To this end, we introduce two quantities which can be easily evaluated, the composite gradient and the implicit noise. Results are established on integrator stability and geometric convergence, and we show that choices of kinetic energy that result in heavy-tailed momentum distributions can exhibit an undesirable negligible moves property, which we define. A general efficiency-robustness trade off is outlined, and implementations which rely on approximate gradients are also discussed. Two numerical studies illustrate our theoretical findings, showing that the standard choice which results in a Gaussian momentum distribution is not always optimal in terms of either robustness or efficiency.
Series This talk is part of the Isaac Newton Institute Seminar Series series.
Included in Lists
- All CMS events
- bld31
- dh539
- Featured lists
- INI info aggregator
- Isaac Newton Institute Seminar Series
- School of Physical Sciences
- Seminar Room 1, Newton Institute
Note: Ex-directory lists are not shown.
![[Talks.cam]](/static/images/talkslogosmall.gif)

Sam Livingstone (University of Bristol)
Wednesday 05 July 2017, 11:00-11:45