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PKDD
2009
Springer
175views Data Mining» more  PKDD 2009»
14 years 3 months ago
Latent Dirichlet Bayesian Co-Clustering
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...
Pu Wang, Carlotta Domeniconi, Kathryn B. Laskey
AAAI
2007
13 years 11 months ago
Unscented Message Passing for Arbitrary Continuous Variables in Bayesian Networks
Since Bayesian network (BN) was introduced in the field of artificial intelligence in 1980s, a number of inference algorithms have been developed for probabilistic reasoning. Ho...
Wei Sun, Kuo-Chu Chang
NECO
2008
134views more  NECO 2008»
13 years 9 months ago
Latent Features in Similarity Judgments: A Nonparametric Bayesian Approach
One of the central problems in cognitive science is determining the mental representations that underlie human inferences. Solutions to this problem often rely on the analysis of ...
Daniel J. Navarro, Thomas L. Griffiths
ICCV
1999
IEEE
14 years 11 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...
ICPR
2002
IEEE
14 years 10 months ago
Boosting and Structure Learning in Dynamic Bayesian Networks for Audio-Visual Speaker Detection
Bayesian networks are an attractive modeling tool for human sensing, as they combine an intuitive graphical representation with ef?cient algorithms for inference and learning. Ear...
Tanzeem Choudhury, James M. Rehg, Vladimir Pavlovi...