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» Probabilistic Inference in Queueing Networks
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IOR
2007
82views more  IOR 2007»
13 years 7 months ago
Compensating for Failures with Flexible Servers
We consider the problem of maximizing capacity in a queueing network with flexible servers, where the classes and servers are subject to failure. We assume that the interarrival ...
Sigrún Andradóttir, Hayriye Ayhan, D...
IJAR
2010
152views more  IJAR 2010»
13 years 6 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
NN
1997
Springer
174views Neural Networks» more  NN 1997»
13 years 12 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
CORR
2010
Springer
118views Education» more  CORR 2010»
13 years 7 months ago
Large scale probabilistic available bandwidth estimation
The common utilization-based definition of available bandwidth and many of the existing tools to estimate it suffer from several important weaknesses: i) most tools report a point...
Frederic Thouin, Mark Coates, Michael G. Rabbat
SIGMETRICS
2000
ACM
107views Hardware» more  SIGMETRICS 2000»
14 years 4 days ago
Detecting shared congestion of flows via end-to-end measurement
Current Internet congestion control protocols operate independently on a per-flow basis. Recent work has demonstrated that cooperative congestion control strategies between flow...
Dan Rubenstein, James F. Kurose, Donald F. Towsley