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» Learning Bayesian Networks with Local Structure
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AAAI
2008
15 years 4 months ago
Markov Blanket Feature Selection for Support Vector Machines
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
Jianqiang Shen, Lida Li, Weng-Keen Wong
ICML
2003
IEEE
16 years 2 months ago
Learning with Knowledge from Multiple Experts
The use of domain knowledge in a learner can greatly improve the models it produces. However, high-quality expert knowledge is very difficult to obtain. Traditionally, researchers...
Matthew Richardson, Pedro Domingos
ICDM
2008
IEEE
156views Data Mining» more  ICDM 2008»
15 years 8 months ago
Exploiting Local and Global Invariants for the Management of Large Scale Information Systems
This paper presents a data oriented approach to modeling the complex computing systems, in which an ensemble of correlation models are discovered to represent the system status. I...
Haifeng Chen, Haibin Cheng, Guofei Jiang, Kenji Yo...
119
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CVIU
2006
158views more  CVIU 2006»
15 years 1 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
113
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AUSAI
2005
Springer
15 years 7 months ago
Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
Peter Vamplew, Robert Ollington