Gibbs sampler and coordinate ascent variational inference: A set-theoretical review

@article{Lee2021GibbsSA,
  title={Gibbs sampler and coordinate ascent variational inference: A set-theoretical review},
  author={Se Yoon Lee},
  journal={Communications in Statistics - Theory and Methods},
  year={2021},
  volume={51},
  pages={1549 - 1568}
}
  • Se Yoon Lee
  • Published 3 August 2020
  • Computer Science
  • Communications in Statistics - Theory and Methods
Abstract One of the fundamental problems in Bayesian statistics is the approximation of the posterior distribution. Gibbs sampler and coordinate ascent variational inference are renownedly utilized approximation techniques that rely on stochastic and deterministic approximations. In this paper, we define fundamental sets of densities frequently used in Bayesian inference. We shall be concerned with the clarification of the two schemes from the set-theoretical point of view. This new way… 
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