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JMLR
2006
169views more  JMLR 2006»
13 years 4 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
PASTE
2010
ACM
13 years 10 months ago
Learning universal probabilistic models for fault localization
Recently there has been significant interest in employing probabilistic techniques for fault localization. Using dynamic dependence information for multiple passing runs, learnin...
Min Feng, Rajiv Gupta
CN
2006
85views more  CN 2006»
13 years 5 months ago
A scalable and decentralized fast-rerouting scheme with efficient bandwidth sharing
This paper focuses on the protection of virtual circuits (Label Switched Paths, LSPs) in a (G)MPLS (Generalised Multi-Protocol Label Switching) network. The proposed algorithm is ...
Simon Balon, Laurent Mélon, Guy Leduc
VLDB
2006
ACM
162views Database» more  VLDB 2006»
14 years 5 months ago
Dependency trees in sub-linear time and bounded memory
We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
Dan Pelleg, Andrew W. Moore