@article{Beaver2012,
abstract = {Abstract: We develop stochastic variational inference , a scalable algorithm for approximating posterior distributions. We develop this technique for a large class of probabilistic models and we demonstrate it with two probabilistic topic models, latent Dirichlet allocation and ...},
archivePrefix = {arXiv},
arxivId = {1206.7051},
author = {Beaver and Clark},
doi = {citeulike-article-id:10852147},
eprint = {1206.7051},
file = {:Users/brekels/Documents/Mendeley Desktop/Stochastic Variational inference - Beaver, Clark.pdf:pdf},
isbn = {1532-4435},
issn = {1532-4435},
journal = {Journal of Machine Learning Research},
number = {2},
pages = {1303--1347},
title = {{Stochastic Variational inference}},
url = {http://arxiv.org/abs/1206.7051$\backslash$npapers2://publication/uuid/D5737928-F59F-43E3-8ADE-53F1831AA866},
volume = {14},
year = {2012}
}

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