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» Exploiting Data Missingness in Bayesian Network Modeling
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CIKM
1997
Springer
15 years 7 months ago
Learning Belief Networks from Data: An Information Theory Based Approach
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
Jie Cheng, David A. Bell, Weiru Liu
UAI
1997
15 years 4 months ago
Score and Information for Recursive Exponential Models with Incomplete Data
Recursive graphical models usually underlie the statistical modelling concerning probabilistic expert systems based on Bayesian networks. This paper de nes a version of these mode...
Bo Thiesson
UAI
1998
15 years 4 months ago
Context-specific approximation in probabilistic inference
There is evidence that the numbers in probabilistic inference don't really matter. This paper considers the idea that we can make a probabilistic model simpler by making fewe...
David Poole
ECCV
2006
Springer
16 years 4 months ago
Learning Nonlinear Manifolds from Time Series
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...
Ruei-Sung Lin, Che-Bin Liu, Ming-Hsuan Yang, Naren...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 3 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...