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BMCBI
2010
229views more  BMCBI 2010»
14 years 10 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
78
Voted
ICN
2005
Springer
15 years 3 months ago
Network Traffic Sampling Model on Packet Identification
Spatially coordinated packet sampling can be implemented by using a deterministic function of packet content to determine the selection decision for a given packet. In this way, a...
Guang Cheng, Jian Gong, Wei Ding 0001
87
Voted
APAQS
2000
IEEE
15 years 2 months ago
Software Quality Prediction Using Mixture Models with EM Algorithm
The use of the statistical technique of mixture model analysis as a tool for early prediction of fault-prone program modules is investigated. The Expectation-Maximum likelihood (E...
Ping Guo, Michael R. Lyu
WSC
2007
15 years 13 days ago
Simulation metamodels for modeling output distribution parameters
Metamodels are functions with calibrated parameters, used actions and simplifications of the simulation model. A metamodel exposes the system’s input-output relationship and ca...
Isabel R. Santos, Pedro R. Santos
ACL
2010
14 years 8 months ago
A Joint Rule Selection Model for Hierarchical Phrase-Based Translation
In hierarchical phrase-based SMT systems, statistical models are integrated to guide the hierarchical rule selection for better translation performance. Previous work mainly focus...
Lei Cui, Dongdong Zhang, Mu Li, Ming Zhou, Tiejun ...