Distributed probabilistic inferencing in sensor networks using variational approximation

DOI10.1016/j.jpdc.2007.07.011zbMath1243.68244OpenAlexW2092444140MaRDI QIDQ436649

Sourav Mukherjee, Hillol Kargupta

Publication date: 26 July 2012

Published in: Journal of Parallel and Distributed Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jpdc.2007.07.011

zbMATH Keywords

data miningvariational approximationsensor networkdistributed data miningprobabilistic inferencing

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Distributed systems (68M14)

Related Items (1)

Distributed Decision‐Tree Induction in Peer‐to‐Peer Systems

Cites Work

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• Estimating network size from local information
• An introduction to variational methods for graphical models
• Data association based on optimization in graphical models with application to sensor networks
• Training Products of Experts by Minimizing Contrastive Divergence
• Learning in Boltzmann Trees

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