Streaming, Distributed Variational Inference for Bayesian Nonparametrics

This paper presents a methodology for creating streaming, distributed inference algorithms for Bayesian nonparametric (BNP) models. In the proposed framework, processing nodes receive a sequence of data minibatches, compute a variational posterior for each, and make asynchronous streaming updates to a central model.

Bibtex

@inproceedings{campbell2015streaming,
  author = {Campbell, Trevor and Straub, Julian and Fisher III, John W. and How, Jonathan},
  title = {Streaming, Distributed Variational Inference for {Bayesian} Nonparametrics},
  year = {2015},
  booktitle = {NIPS}
}