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» Learning Causal Structure from Overlapping Variable Sets
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IJCAI
2007
13 years 9 months ago
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
CIDM
2009
IEEE
14 years 2 months ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...
SDM
2011
SIAM
232views Data Mining» more  SDM 2011»
12 years 10 months ago
A Sequential Dual Method for Structural SVMs
In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to computationa...
Shirish Krishnaj Shevade, Balamurugan P., S. Sunda...
ISBI
2002
IEEE
14 years 8 months ago
Statistical shape model for automatic skull-stripping of brain images
This paper presents a statistical shape model for automatic skull stripping of MR brain images. A surface model of the brain boundary is hierarchically represented by a set of ove...
Zhiqiang Lao, Dinggang Shen, Christos Davatzikos
GCB
2008
Springer
174views Biometrics» more  GCB 2008»
13 years 8 months ago
Lightweight Comparison of RNAs based on Exact Sequence-structure Matches
: Specific functions of RNA molecules are often associated with different motifs in the RNA structure. The key feature that forms such an RNA motif is the combination of sequence ...
Steffen Heyne, Sebastian Will, Michael Beckstette,...