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» An Improved LAZY-AR Approach to Bayesian Network Inference
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AAAI
2006
13 years 6 months ago
Performing Incremental Bayesian Inference by Dynamic Model Counting
The ability to update the structure of a Bayesian network when new data becomes available is crucial for building adaptive systems. Recent work by Sang, Beame, and Kautz (AAAI 200...
Wei Li 0002, Peter van Beek, Pascal Poupart
ATAL
2008
Springer
13 years 7 months ago
Efficient approximate inference in distributed Bayesian networks for MAS-based sensor interpretation
The multiply sectioned Bayesian network (MSBN) framework is the most studied approach for distributed Bayesian Network inference in an MAS setting. This paper describes a new fram...
Norman Carver
AI
2006
Springer
13 years 5 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth
INFOCOM
2010
IEEE
13 years 3 months ago
Bayesian Inference for Localization in Cellular Networks
—In this paper, we present a general technique based on Bayesian inference to locate mobiles in cellular networks. We study the problem of localizing users in a cellular network ...
Hui Zang, François Baccelli, Jean Bolot
AI
2010
Springer
13 years 5 months ago
Understanding the scalability of Bayesian network inference using clique tree growth curves
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
Ole J. Mengshoel