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Asynchronous Stochastic Gradient MCMC with Elastic Coupling
[article]
2016
arXiv
pre-print
We consider parallel asynchronous Markov Chain Monte Carlo (MCMC) sampling for problems where we can leverage (stochastic) gradients to define continuous dynamics which explore the target distribution. We outline a solution strategy for this setting based on stochastic gradient Hamiltonian Monte Carlo sampling (SGHMC) which we alter to include an elastic coupling term that ties together multiple MCMC instances. The proposed strategy turns inherently sequential HMC algorithms into asynchronous
arXiv:1612.00767v2
fatcat:s5qk5sq4grb7nj44exvmo72iki