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INFOCOM
2008
IEEE
14 years 1 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, ...
FLAIRS
2009
13 years 5 months ago
Multiagent Bayesian Forecasting of Time Series with Graphical Models
Time series are found widely in engineering and science. We study multiagent forecasting in time series, drawing from literature on time series, graphical models, and multiagent s...
Yang Xiang, James Smith, Jeff Kroes
BMCBI
2010
147views more  BMCBI 2010»
13 years 7 months ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
CORR
2012
Springer
210views Education» more  CORR 2012»
12 years 3 months ago
Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks
Markov jump processes and continuous time Bayesian networks are important classes of continuous time dynamical systems. In this paper, we tackle the problem of inferring unobserve...
Vinayak Rao, Yee Whye Teh
BMCBI
2005
126views more  BMCBI 2005»
13 years 7 months ago
HomoMINT: an inferred human network based on orthology mapping of protein interactions discovered in model organisms
Background: The application of high throughput approaches to the identification of protein interactions has offered for the first time a glimpse of the global interactome of some ...
Maria Persico, Arnaud Ceol, Caius Gavrila, Robert ...