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139
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WACV
2005
IEEE
15 years 9 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
151
Voted
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
15 years 5 months ago
Clustering from Constraint Graphs
In constrained clustering it is common to model the pairwise constraints as edges on the graph of observations. Using results from graph theory, we analyze such constraint graphs ...
Ari Freund, Dan Pelleg, Yossi Richter
113
Voted
NOMS
2002
IEEE
127views Communications» more  NOMS 2002»
15 years 8 months ago
Intelligent search of correlated alarms from database containing noise data
Alarm correlation plays an important role in improving the service and reliability in modern telecommunication networks. Most previous research of alarm correlation didn’t consi...
Qingguo Zheng, Ke Xu, Weifeng Lv, Shilong Ma
135
Voted
PKDD
2005
Springer
161views Data Mining» more  PKDD 2005»
15 years 9 months ago
Active Sampling for Knowledge Discovery from Biomedical Data
Abstract. We describe work aimed at cost-constrained knowledge discovery in the biomedical domain. To improve the diagnostic/prognostic models of cancer, new biomarkers are studied...
Sriharsha Veeramachaneni, Francesca Demichelis, Em...
134
Voted
AI
2002
Springer
15 years 3 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...