On Bayesian Network Inference with Simple Propagation

Cory J. Butz, Jhonatan S. Oliveira, André E. dos Santos, Anders L. Madsen
Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:62-73, 2016.

Abstract

\emphSimple Propagation (SP) was recently proposed as a new join tree propagation algorithm for exact inference in discrete Bayesian networks and empirically shown to be faster than \emphLazy Propagation (LP) when applied on optimal (or close to) join trees built from real-world and benchmark Bayesian networks. This paper extends SP in two directions. First, we propose and empirically evaluate eight heuristics for determining elimination orderings in SP. Second, we show that the relevant potentials in SP are precisely those in LP.

Cite this Paper

BibTeX
@InProceedings{pmlr-v52-butz16a, title = {On {B}ayesian Network Inference with Simple Propagation}, author = {Butz, Cory J. and Oliveira, Jhonatan S. and Santos, André E. dos and Madsen, Anders L.}, booktitle = {Proceedings of the Eighth International Conference on Probabilistic Graphical Models}, pages = {62--73}, year = {2016}, editor = {Antonucci, Alessandro and Corani, Giorgio and Campos}, Cassio Polpo}, volume = {52}, series = {Proceedings of Machine Learning Research}, address = {Lugano, Switzerland}, month = {06--09 Sep}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v52/butz16a.pdf}, url = {https://proceedings.mlr.press/v52/butz16a.html}, abstract = {\emphSimple Propagation (SP) was recently proposed as a new join tree propagation algorithm for exact inference in discrete Bayesian networks and empirically shown to be faster than \emphLazy Propagation (LP) when applied on optimal (or close to) join trees built from real-world and benchmark Bayesian networks. This paper extends SP in two directions. First, we propose and empirically evaluate eight heuristics for determining elimination orderings in SP. Second, we show that the relevant potentials in SP are precisely those in LP.} }
Endnote
%0 Conference Paper %T On Bayesian Network Inference with Simple Propagation %A Cory J. Butz %A Jhonatan S. Oliveira %A André E. dos Santos %A Anders L. Madsen %B Proceedings of the Eighth International Conference on Probabilistic Graphical Models %C Proceedings of Machine Learning Research %D 2016 %E Alessandro Antonucci %E Giorgio Corani %E Cassio Polpo Campos} %F pmlr-v52-butz16a %I PMLR %P 62--73 %U https://proceedings.mlr.press/v52/butz16a.html %V 52 %X \emphSimple Propagation (SP) was recently proposed as a new join tree propagation algorithm for exact inference in discrete Bayesian networks and empirically shown to be faster than \emphLazy Propagation (LP) when applied on optimal (or close to) join trees built from real-world and benchmark Bayesian networks. This paper extends SP in two directions. First, we propose and empirically evaluate eight heuristics for determining elimination orderings in SP. Second, we show that the relevant potentials in SP are precisely those in LP.
RIS
TY - CPAPER TI - On Bayesian Network Inference with Simple Propagation AU - Cory J. Butz AU - Jhonatan S. Oliveira AU - André E. dos Santos AU - Anders L. Madsen BT - Proceedings of the Eighth International Conference on Probabilistic Graphical Models DA - 2016/08/15 ED - Alessandro Antonucci ED - Giorgio Corani ED - Cassio Polpo Campos} ID - pmlr-v52-butz16a PB - PMLR DP - Proceedings of Machine Learning Research VL - 52 SP - 62 EP - 73 L1 - http://proceedings.mlr.press/v52/butz16a.pdf UR - https://proceedings.mlr.press/v52/butz16a.html AB - \emphSimple Propagation (SP) was recently proposed as a new join tree propagation algorithm for exact inference in discrete Bayesian networks and empirically shown to be faster than \emphLazy Propagation (LP) when applied on optimal (or close to) join trees built from real-world and benchmark Bayesian networks. This paper extends SP in two directions. First, we propose and empirically evaluate eight heuristics for determining elimination orderings in SP. Second, we show that the relevant potentials in SP are precisely those in LP. ER -
APA
Butz, C.J., Oliveira, J.S., Santos, A.E.d. & Madsen, A.L.. (2016). On Bayesian Network Inference with Simple Propagation. Proceedings of the Eighth International Conference on Probabilistic Graphical Models, in Proceedings of Machine Learning Research 52:62-73 Available from https://proceedings.mlr.press/v52/butz16a.html.

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