Exploiting within-Clique factorizations in junction-tree algorithms
McAuley, Julian; Caetano, Tiberio
Description
We show that the expected computational complexity of the Junction-Tree Algorithm for maximum a posteriori inference in graphical models can be improved. Our results apply whenever the potentials over maximal cliques of the triangulated graph are factored over subcliques. This is common in many real applications, as we illustrate with several examples. The new algorithms are easily implemented, and experiments show substantial speed-ups over the classical Junction-Tree Algorithm. This enlarges...[Show more]
dc.contributor.author | McAuley, Julian | |
---|---|---|
dc.contributor.author | Caetano, Tiberio | |
dc.coverage.spatial | Sardinia Italy | |
dc.date.accessioned | 2015-12-10T22:43:45Z | |
dc.date.created | May 13-15 2010 | |
dc.identifier.uri | http://hdl.handle.net/1885/58301 | |
dc.description.abstract | We show that the expected computational complexity of the Junction-Tree Algorithm for maximum a posteriori inference in graphical models can be improved. Our results apply whenever the potentials over maximal cliques of the triangulated graph are factored over subcliques. This is common in many real applications, as we illustrate with several examples. The new algorithms are easily implemented, and experiments show substantial speed-ups over the classical Junction-Tree Algorithm. This enlarges the class of models for which exact inference is efficient. | |
dc.publisher | Society for Artificial Intelligence and Statistics | |
dc.relation.ispartofseries | International Conference on Artificial Intelligence and Statistics (AISTATS 2010) | |
dc.source | Proceedings of The 13th International Conference on Artificial Intelligence and Statistics(AISTATS-2010) | |
dc.source.uri | http://jmlr.csail.mit.edu/proceedings/papers/v9 | |
dc.subject | Keywords: Exact inference; GraphicaL model; Maximal clique; Maximum a posteriori; Real applications; Algorithms; Artificial intelligence; Forestry; Algorithms; Artificial Intelligence; Forestry | |
dc.title | Exploiting within-Clique factorizations in junction-tree algorithms | |
dc.type | Conference paper | |
local.description.notes | Imported from ARIES | |
local.description.refereed | Yes | |
dc.date.issued | 2010 | |
local.identifier.absfor | 080109 - Pattern Recognition and Data Mining | |
local.identifier.ariespublication | u8803936xPUB436 | |
local.type.status | Published Version | |
local.contributor.affiliation | McAuley, Julian, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Caetano, Tiberio, College of Engineering and Computer Science, ANU | |
local.description.embargo | 2037-12-31 | |
local.bibliographicCitation.startpage | 525 | |
local.bibliographicCitation.lastpage | 532 | |
dc.date.updated | 2016-02-24T11:45:03Z | |
local.identifier.scopusID | 2-s2.0-84860172533 | |
Collections | ANU Research Publications |
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01_McAuley_Exploiting_within-Clique_2010.pdf | 1.99 MB | Adobe PDF | Request a copy |
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