• Corpus ID: 167217296

Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates

@inproceedings{Salim2019StochasticPL,
  title={Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates},
  author={Adil Salim and D. Kovalev and Peter Richt{\'a}rik},
  booktitle={NeurIPS},
  year={2019}
}
We propose a new algorithm---Stochastic Proximal Langevin Algorithm (SPLA)---for sampling from a log concave distribution. Our method is a generalization of the Langevin algorithm to potentials expressed as the sum of one stochastic smooth term and multiple stochastic nonsmooth terms. In each iteration, our splitting technique only requires access to a stochastic gradient of the smooth term and a stochastic proximal operator for each of the nonsmooth terms. We establish nonasymptotic sublinear… 

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