NeurIPS 2019spotlight18 citations
Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay
Abstract
Belief propagation is a fundamental message-passing algorithm for probabilistic reasoning and inference in graphical models. While it is known to be exact on trees, in most applications belief propagation is run on graphs with cycles. Understanding the behavior of
BibTeX
@inproceedings{NEURIPS2019_573f7f25,
author = {Koehler, Frederic},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay},
url = {https://proceedings.neurips.cc/paper_files/paper/2019/file/573f7f25b7b1eb79a4ec6ba896debefd-Paper.pdf},
volume = {32},
year = {2019}
}