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UAI
2004
13 years 10 months ago
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Iain Murray, Zoubin Ghahramani
MOBIHOC
2006
ACM
14 years 8 months ago
Robust distributed node localization with error management
Location knowledge of nodes in a network is essential for many tasks such as routing, cooperative sensing, or service delivery in ad hoc, mobile, or sensor networks. This paper in...
Juan Liu, Ying Zhang, Feng Zhao
IPSN
2010
Springer
14 years 27 days ago
Practical modeling and prediction of radio coverage of indoor sensor networks
The robust operation of many sensor network applications depends on deploying relays to ensure wireless coverage. Radio mapping aims to predict network coverage based on a small n...
Octav Chipara, Gregory Hackmann, Chenyang Lu, Will...
ICIAP
2007
ACM
14 years 9 months ago
An information theoretic rule for sample size adaptation in particle filtering
To become robust, a tracking algorithm must be able to support uncertainty and ambiguity often inherently present in the data in form of occlusion and clutter. This comes usually ...
Oswald Lanz
ESWS
2009
Springer
14 years 3 months ago
Neighborhood-Based Tag Prediction
We consider the problem of tag prediction in collaborative tagging systems where users share and annotate resources on the Web. We put forward HAMLET, a novel approach to automatic...
Adriana Budura, Sebastian Michel, Philippe Cudr&ea...