Paper Info
Title
The Complexity of Plate Probabilistic Models.
Abstract
Plate-based probabilistic models combine a few relational constructs with Bayesian networks, so as to allow one to specify large and repetitive probabilistic networks in a compact and intuitive manner. In this paper we investigate the combined, data and domain complexity of plate models, showing that they range from polynomial to #P-complete to #EXP-complete.
Year
DOI
Venue
2015
10.1007/978-3-319-23540-0_3
Lecture Notes in Artificial Intelligence
Field
DocType
Volume
Polynomial,Computer science,Probabilistic CTL,Theoretical computer science,Probabilistic analysis of algorithms,Bayesian network,Artificial intelligence,Probabilistic logic,Machine learning,Probabilistic networks
Conference
9310
ISSN
Citations 
PageRank 
0302-9743
2
0.37
References 
Authors
4
2
Name
Order
Citations
PageRank
Fábio Cozman11810.16
Denis Deratani Mauá216524.64