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NIPS
2003
15 years 1 months ago
Approximate Expectation Maximization
We discuss the integration of the expectation-maximization (EM) algorithm for maximum likelihood learning of Bayesian networks with belief propagation algorithms for approximate i...
Tom Heskes, Onno Zoeter, Wim Wiegerinck
IJCAI
2003
15 years 1 months ago
When Discriminative Learning of Bayesian Network Parameters Is Easy
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
Hannes Wettig, Peter Grünwald, Teemu Roos, Pe...
AAAI
2006
15 years 1 months ago
Probabilistic Self-Localization for Sensor Networks
This paper describes a technique for the probabilistic self-localization of a sensor network based on noisy inter-sensor range data. Our method is based on a number of parallel in...
Dimitri Marinakis, Gregory Dudek
IJBIDM
2006
78views more  IJBIDM 2006»
14 years 11 months ago
Appraisal of companies with Bayesian networks
: Appraisal of companies is an important business activity. We mainly apply Bayesian networks for this classification task for Japanese electric company data. Firstly, few standard...
Priyantha Wijayatunga, Shigeru Mase, Masanori Naka...
ICASSP
2011
IEEE
14 years 3 months ago
Convergence of a distributed parameter estimator for sensor networks with local averaging of the estimates
The paper addresses the convergence of a decentralized Robbins-Monro algorithm for networks of agents. This algorithm combines local stochastic approximation steps for finding th...
Pascal Bianchi, Gersende Fort, Walid Hachem, J&eac...