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» Bayesian learning of measurement and structural models
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CVPR
2005
IEEE
14 years 11 months ago
A Bayesian Approach to Unsupervised Feature Selection and Density Estimation Using Expectation Propagation
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
Shaorong Chang, Nilanjan Dasgupta, Lawrence Carin
BMCBI
2008
118views more  BMCBI 2008»
13 years 9 months ago
Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling
Background: With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few appro...
Grace S. Shieh, Chung-Ming Chen, Ching-Yun Yu, Jui...
ICCV
2007
IEEE
14 years 11 months ago
Learning Structured Appearance Models from Captioned Images of Cluttered Scenes
Given an unstructured collection of captioned images of cluttered scenes featuring a variety of objects, our goal is to learn both the names and appearances of the objects. Only a...
Michael Jamieson, Afsaneh Fazly, Sven J. Dickinson...
IJCAI
2007
13 years 10 months ago
Representations for Action Selection Learning from Real-Time Observation of Task Experts
The association of perception and action is key to learning by observation in general, and to programlevel task imitation in particular. The question is how to structure this info...
Mark A. Wood, Joanna Bryson
UAI
2003
13 years 10 months ago
The Revisiting Problem in Mobile Robot Map Building: A Hierarchical Bayesian Approach
We present an application of hierarchical Bayesian estimation to robot map building. The revisiting problem occurs when a robot has to decide whether it is seeing a previously-bui...
Benjamin Stewart, Jonathan Ko, Dieter Fox, Kurt Ko...