Loopy Belief Propagation for Approximate Inference: An Empirical Study

@inproceedings{citeulike:1689781, abstract = {Recently, researchers have demonstrated that "loopy belief propagation" --- the use of Pearl's polytree algorithm in a Bayesian network with loops --- can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performance of "Turbo Codes" --- codes whose decoding algorithm is equivalent to loopy belief propagation in a chain-structured Bayesian network. In this paper we ask: is there something special about the...}, author = {Murphy, K. P. and Weiss, Y. and Jordan, M. }, booktitle = {Uncertainty in Artificial Intelligence}, citeulike-article-id = {1689781}, pages = {467--475}, posted-at = {2008-06-03 18:13:38}, priority = {2}, title = {Loopy Belief Propagation for Approximate Inference: An Empirical Study}, url = {http://citeseer.ist.psu.edu/murphy99loopy.html}, year = {1999} }

TY - CONF ID - citeulike:1689781 L3 - citeulike-article-id:1689781 TI - Loopy Belief Propagation for Approximate Inference: An Empirical Study T2 - Uncertainty in Artificial Intelligence SP - 467 EP - 475 N2 - Recently, researchers have demonstrated that "loopy belief propagation" --- the use of Pearl's polytree algorithm in a Bayesian network with loops --- can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performance of "Turbo Codes" --- codes whose decoding algorithm is equivalent to loopy belief propagation in a chain-structured Bayesian network. In this paper we ask: is there something special about the... AU - Murphy, KP AU - Weiss, Y AU - Jordan, M PY - 1999/// UR - http://citeseer.ist.psu.edu/murphy99loopy.html ER -