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» Compiling Bayesian Networks Using Variable Elimination
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ICDM
2005
IEEE
116views Data Mining» more  ICDM 2005»
14 years 1 months ago
Learning Functional Dependency Networks Based on Genetic Programming
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
CVPR
2012
IEEE
11 years 10 months ago
Sum-product networks for modeling activities with stochastic structure
This paper addresses recognition of human activities with stochastic structure, characterized by variable spacetime arrangements of primitive actions, and conducted by a variable ...
Mohamed R. Amer, Sinisa Todorovic
PLDI
2004
ACM
14 years 27 days ago
Balancing register allocation across threads for a multithreaded network processor
+ Modern network processors employ multi-threading to allow concurrency amongst multiple packet processing tasks. We studied the properties of applications running on the network p...
Xiaotong Zhuang, Santosh Pande
ICML
2004
IEEE
14 years 8 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
JAIR
2010
119views more  JAIR 2010»
13 years 6 months ago
Active Tuples-based Scheme for Bounding Posterior Beliefs
The paper presents a scheme for computing lower and upper bounds on the posterior marginals in Bayesian networks with discrete variables. Its power lies in its ability to use any ...
Bozhena Bidyuk, Rina Dechter, Emma Rollon