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» Minerva: Learning to Infer Network Path Properties
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INFOCOM
2008
IEEE
13 years 11 months ago
Minerva: Learning to Infer Network Path Properties
—Knowledge of the network path properties such as latency, hop count, loss and bandwidth is key to the performance of overlay networks, grids and p2p applications. Network operat...
Rita H. Wouhaybi, Puneet Sharma, Sujata Banerjee, ...
MLG
2007
Springer
13 years 11 months ago
Inferring Vertex Properties from Topology in Large Networks
: Network topology not only tells about tightly-connected “communities,” but also gives cues on more subtle properties of the vertices. We introduce a simple probabilistic late...
Janne Sinkkonen, Janne Aukia, Samuel Kaski
TITS
2011
165views more  TITS 2011»
12 years 12 months ago
Robust Inference of Principal Road Paths for Intelligent Transportation Systems
Abstract—Over the last few years, electronic vehicle guidance systems have become increasingly more popular. However, despite their ubiquity, performance will always be subject t...
Gabriel Agamennoni, Juan Nieto, Eduardo Mario Nebo...
JMLR
2011
145views more  JMLR 2011»
13 years 1 hour ago
Cumulative Distribution Networks and the Derivative-sum-product Algorithm: Models and Inference for Cumulative Distribution Func
We present a class of graphical models for directly representing the joint cumulative distribution function (CDF) of many random variables, called cumulative distribution networks...
Jim C. Huang, Brendan J. Frey
TON
2010
167views more  TON 2010»
12 years 11 months ago
A Machine Learning Approach to TCP Throughput Prediction
TCP throughput prediction is an important capability in wide area overlay and multi-homed networks where multiple paths may exist between data sources and receivers. In this paper...
Mariyam Mirza, Joel Sommers, Paul Barford, Xiaojin...