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Recently, we and several other authors have written about the possibilities of using stochastic approximation techniques for fitting variational approximations to intractable Bayesian posterior distributions.
“A Stochastic Approximation Method.”
Robbins, H. and Monro, S. (1951) · 1951
Earlier work this paper cites.
“Stochastic Variational Inference.”
Hoffman, M., Blei, D., Wang, C., and Paisley, J. (2012) · 2012
Earlier work this paper cites.
“Regression density estimation with variational methods and stochastic approximation.”
Nott, D., Tan, S., Villani, M., and Kohn, R. (2012) · 2012
Earlier work this paper cites.
“Variational Bayesian Inference with Stochastic Search.”
Paisley, J., Blei, D., and Jordan, M. (2012) · 2012
Cited alongside, same era.
“Auto-Encoding Variational Bayes.”
Kingma, D. P. and Welling, M. (2013) · 2013
Cited alongside, same era.
“Black Box Variational Inference.”
Ranganath, R., Gerrish, S., and Blei, D. M. (2013) · 2013
Cited alongside, same era.
“Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression.”
Salimans, T. and Knowles, D. A. (2013) · 2013
Later among the works it cites.
“Automated Variational Inference in Probabilistic Programming.”
Wingate, D. and Weber, T. (2013) · 2013
Later among the works it cites.
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