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JAIR
2007
112views more  JAIR 2007»
13 years 9 months ago
Cutset Sampling for Bayesian Networks
The paper presents a new sampling methodology for Bayesian networks that samples only a subset of variables and applies exact inference to the rest. Cutset sampling is a network s...
Bozhena Bidyuk, Rina Dechter
JMLR
2010
125views more  JMLR 2010»
13 years 3 months ago
Continuous Time Bayesian Network Reasoning and Learning Engine
We present a continuous time Bayesian network reasoning and learning engine (CTBN-RLE). A continuous time Bayesian network (CTBN) provides a compact (factored) description of a co...
Christian R. Shelton, Yu Fan, William Lam, Joon Le...
ICASSP
2011
IEEE
13 years 25 days ago
Directional descriptors using zernike moment phases for object orientation estimation in underwater sonar images
Conventional methods for rotation angle estimation are not very robust to variations in object shape or intensity. However in real object recognition scenarios like in underwater ...
Naveen Kumar, Adam C. Lammert, Brendan Englot, Fra...
NIPS
2000
13 years 10 months ago
On Reversing Jensen's Inequality
Jensen's inequality is a powerful mathematical tool and one of the workhorses in statistical learning. Its applications therein include the EM algorithm, Bayesian estimation ...
Tony Jebara, Alex Pentland
ECSQARU
2007
Springer
14 years 3 months ago
Logical Compilation of Bayesian Networks with Discrete Variables
This paper presents a new approach to inference in Bayesian networks. The principal idea is to encode the network by logical sentences and to compile the resulting encoding into an...
Michael Wachter, Rolf Haenni