Stratified stochastic variational inference for high-dimensional network factor model

  title={Stratified stochastic variational inference for high-dimensional network factor model},
  author={Emanule Aliverti and Massimiliano Russo},
  journal={Journal of Computational and Graphical Statistics},
There has been considerable recent interest in Bayesian modeling of high-dimensional networks via latent space approaches. When the number of nodes increases, estimation based on Markov Chain Monte Carlo can be extremely slow and show poor mixing, thereby motivating research on alternative algorithms that scale well in high-dimensional settings. In this article, we focus on the latent factor model, a widely used approach for latent space modeling of network data. We develop scalable algorithms… 

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