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CIDM
2007
IEEE
15 years 10 months ago
K2GA: Heuristically Guided Evolution of Bayesian Network Structures from Data
— We present K2GA, an algorithm for learning Bayesian network structures from data. K2GA uses a genetic algorithm to perform stochastic search, while employing a modified versio...
Eli Faulkner
IJAR
2006
89views more  IJAR 2006»
15 years 4 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
CVPR
1999
IEEE
16 years 6 months ago
Integrating Shape from Shading and Range Data Using Neural Networks
This paper presents a framework for integrating multiple sensory data, sparse range data and dense depth maps from shape from shading in order to improve the 3D reconstruction of ...
Mostafa G.-H. Mostafa, Sameh M. Yamany, Aly A. Far...
ISCI
1998
83views more  ISCI 1998»
15 years 4 months ago
On Generalization by Neural Networks
We report new results on the corner classification approach to training feedforward neural networks. It is shown that a prescriptive learning procedure where the weights are simp...
Subhash C. Kak
RECOMB
2000
Springer
15 years 8 months ago
Using Bayesian networks to analyze expression data
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a "snapshot" of transcription levels within the c...
Nir Friedman, Michal Linial, Iftach Nachman, Dana ...