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Implicit Langevin Algorithms for Sampling From Log-concave Densities
[article]
2021
arXiv
pre-print
For sampling from a log-concave density, we study implicit integrators resulting from θ-method discretization of the overdamped Langevin diffusion stochastic differential equation. Theoretical and algorithmic properties of the resulting sampling methods for θ∈ [0,1] and a range of step sizes are established. Our results generalize and extend prior works in several directions. In particular, for θ≥1/2, we prove geometric ergodicity and stability of the resulting methods for all step sizes. We
arXiv:1903.12322v2
fatcat:taby5mkhf5cjpcdkgc6h4op6wq