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TMC
2010
104views more  TMC 2010»
15 years 4 months ago
On Nodal Encounter Patterns in Wireless LAN Traces
—In this paper we analyze multiple wireless LAN (WLAN) traces from university and corporate campuses. In particular, we consider an important event between mobile nodes in wirele...
Wei-jen Hsu, Ahmed Helmy
GLOBECOM
2007
IEEE
16 years 1 days ago
Loss Tomography in General Topologies with Network Coding
Abstract— Network tomography infers internal network characteristics by sending and collecting probe packets from the network edge. Traditional tomographic techniques for general...
Minas Gjoka, Christina Fragouli, Pegah Sattari, At...
SP
2008
IEEE
176views Security Privacy» more  SP 2008»
16 years 2 days ago
Casting out Demons: Sanitizing Training Data for Anomaly Sensors
The efficacy of Anomaly Detection (AD) sensors depends heavily on the quality of the data used to train them. Artificial or contrived training data may not provide a realistic v...
Gabriela F. Cretu, Angelos Stavrou, Michael E. Loc...
NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 10 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
MMMACNS
2005
Springer
15 years 11 months ago
Networks, Markov Lie Monoids, and Generalized Entropy
The continuous general linear group in n dimensions can be decomposed into two Lie groups: (1) an n(n-1) dimensional ‘Markov type’ Lie group that is defined by preserving the ...
Joseph E. Johnson