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» Complexity of Inference in Graphical Models
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LREC
2010
166views Education» more  LREC 2010»
13 years 10 months ago
Learning Based Java for Rapid Development of NLP Systems
Today's natural language processing systems are growing more complex with the need to incorporate a wider range of language resources and more sophisticated statistical metho...
Nick Rizzolo, Dan Roth
CVIU
2006
158views more  CVIU 2006»
13 years 9 months ago
Sequential mean field variational analysis of structured deformable shapes
A novel approach is proposed to analyzing and tracking the motion of structured deformable shapes, which consist of multiple correlated deformable subparts. Since this problem is ...
Gang Hua, Ying Wu
PRL
2000
182views more  PRL 2000»
13 years 8 months ago
Bayesian MLP neural networks for image analysis
We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...
Aki Vehtari, Jouko Lampinen
JCB
2002
93views more  JCB 2002»
13 years 8 months ago
Unfolding of Microarray Data
The use of DNA microarrays for the analysis of complex biological samples is becoming a mainstream part of biomedical research. One of the most commonly used methods compares the ...
Andrew B. Goryachev, Pascale F. Macgregor, Aled M....
JAIR
2010
145views more  JAIR 2010»
13 years 7 months ago
Planning with Noisy Probabilistic Relational Rules
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
Tobias Lang, Marc Toussaint