Expectation propagation for approximate inference in dynamic Bayesian networks Export

@inproceedings{citeulike:3370921, abstract = {We describe expectation propagation for approximate inference in dynamic Bayesian networks as a natural extension of Pearl\&\#039;s exact belief propagation. Expectation propagation is a greedy algorithm, converges in many practical cases, but not always. We derive a double-loop algorithm, guaranteed to converge to a local minimum of a Bethe free energy. Furthermore, we show that stable xed points of (damped) expectation propagation correspond to local minima of this free energy, but that the converse need not be the case. We illustrate the algorithms by applying them to switching linear dynamical systems and discuss implications for approximate inference in general Bayesian networks. 1}, author = {Heskes, Tom and Zoeter, Onno}, booktitle = {In Proceedings UAI}, citeulike-article-id = {3370921}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.5450}, keywords = {expectation-propagation, switching-linear-dynamical}, pages = {216--223}, posted-at = {2008-10-19 19:24:24}, priority = {2}, title = {Expectation propagation for approximate inference in dynamic Bayesian networks}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.5450}, year = {2002} }

TY - CONF ID - citeulike:3370921 L3 - citeulike-article-id:3370921 N2 - We describe expectation propagation for approximate inference in dynamic Bayesian networks as a natural extension of Pearl's exact belief propagation. Expectation propagation is a greedy algorithm, converges in many practical cases, but not always. We derive a double-loop algorithm, guaranteed to converge to a local minimum of a Bethe free energy. Furthermore, we show that stable xed points of (damped) expectation propagation correspond to local minima of this free energy, but that the converse need not be the case. We illustrate the algorithms by applying them to switching linear dynamical systems and discuss implications for approximate inference in general Bayesian networks. 1 EP - 223 TI - Expectation propagation for approximate inference in dynamic Bayesian networks T2 - In Proceedings UAI SP - 216 KW - expectation-propagation KW - switching-linear-dynamical AU - Heskes, Tom AU - Zoeter, Onno PY - 2002/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.5450 ER -