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» Compiling relational Bayesian networks for exact inference
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UAI
2008
13 years 10 months ago
Hybrid Variational/Gibbs Collapsed Inference in Topic Models
Variational Bayesian inference and (collapsed) Gibbs sampling are the two important classes of inference algorithms for Bayesian networks. Both have their advantages and disadvant...
Max Welling, Yee Whye Teh, Bert Kappen
HYBRID
2000
Springer
14 years 6 days ago
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham
KES
2005
Springer
14 years 2 months ago
Bayesian Inference Driven Behavior Network Architecture for Avoiding Moving Obstacles
This paper presents a technique for an intelligent robot to adaptively behave in unforeseen and dynamic circumstances. Since the traditional methods utilized the relatively reliabl...
Hyeun-Jeong Min, Sung-Bae Cho
GLOBECOM
2010
IEEE
13 years 6 months ago
A Graphical Framework for Spectrum Modeling and Decision Making in Cognitive Radio Networks
There are many key problems of decision making related to spectrum occupancies in cognitive radio networks. It is known that there exist correlations of spectrum occupancies in tim...
Husheng Li, Robert C. Qiu
ICCV
1999
IEEE
14 years 10 months ago
A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic Models
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and synthesizing figure motion has employed eit...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Ke...