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CVPR
2008
IEEE
16 years 2 months ago
Learning Bayesian Networks with qualitative constraints
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
Yan Tong, Qiang Ji
DIS
2009
Springer
15 years 7 months ago
An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting
Within-network regression addresses the task of regression in partially labeled networked data where labels are sparse and continuous. Data for inference consist of entities associ...
Annalisa Appice, Michelangelo Ceci, Donato Malerba
TJS
2010
182views more  TJS 2010»
14 years 11 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
134
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SOCIALCOM
2010
14 years 7 months ago
Learning Influence Propagation of Personal Blogs with Content and Network Analyses
Weblogs (blogs) serve as a gateway to a large blog reader population, so blog authors can potentially influence a large reader population by expressing their thoughts and expertise...
Il-Chul Moon, Dongwoo Kim, Yohan Jo, Alice H. Oh
BMCBI
2010
154views more  BMCBI 2010»
15 years 21 days ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...