Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction

Difan Zou, Pan Xu, Quanquan Gu

Neural Information Processing Systems 

We provide a convergence analysis of SRVR-HMC for sampling from a class of non-log-concave distributions and show that SRVR-HMC converges faster than all existing HMC-type algorithms based on underdamped Langevin dynamics.

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