mlsanityData to 7 Oct 2026

On the Dissipation of Ideal Hamiltonian Monte Carlo Sampler

arXiv 2209.07438 ↗First posted 15 Sep 2022stat.CO stat.MLcited by 1

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Abstract (arXiv)

We report on what seems to be an intriguing connection between variable integration time and partial velocity refreshment of Ideal Hamiltonian Monte Carlo samplers, both of which can be used for reducing the dissipative behavior of the dynamics. More concretely, we show that on quadratic potentials, efficiency can be improved through these means by a √kappa factor in Wasserstein-2 distance, compared to classical constant integration time, fully refreshed HMC. We additionally explore the benefit of randomized integrators for simulating the Hamiltonian dynamics under higher order regularity conditions.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 5 of its 17 references that are in the map. First posted on arXiv 15 Sep 2022.

Builds on

5 of 17 references.

References · 5

  1. 2018On sampling from a log-concave density using kinetic Langevin diffusionscited by 61
  2. 2019Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributionscited by 28
  3. 2021Mixing Time Guarantees for Unadjusted Hamiltonian Monte Carlocited by 18
  4. 2021An Introduction to Hamiltonian Monte Carlo Method for Samplingcited by 8
  5. 2022Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Timecited by 7

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Citing papers per year: 2022: 1.

1 paper.