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ICML
2000
IEEE
16 years 5 months ago
Learning Bayesian Networks for Diverse and Varying numbers of Evidence Sets
We introduce an expandable Bayesian network (EBN) to handle the combination of diverse multiple homogeneous evidence sets. An EBN is an augmented Bayesian network which instantiat...
Zu Whan Kim, Ramakant Nevatia
TJS
2010
182views more  TJS 2010»
15 years 2 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
WMTE
2006
IEEE
15 years 10 months ago
A Framework for Interoperability with VLEs for Large Scale Deployment of Mobile Learning
The diversity of mobile devices and their limitations have raised many challenges for the actual deployment of mobile learning across institutions. The main objective of this work...
Fatma Elsayed Meawad, Geneen Stubbs
JMLR
2006
131views more  JMLR 2006»
15 years 4 months ago
Incremental Support Vector Learning: Analysis, Implementation and Applications
Incremental Support Vector Machines (SVM) are instrumental in practical applications of online learning. This work focuses on the design and analysis of efficient incremental SVM ...
Pavel Laskov, Christian Gehl, Stefan Krüger, ...
ECIS
2004
15 years 5 months ago
Value-based business modelling for network organizations: lessons learned from the electricity sector
Speed and availability of information, delivered in past years by Internet technologies, made it easier for any company to outsource primary activities, which resulted in unbundli...
Vera Kartseva, Jaap Gordijn, Yao-Hua Tan