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» Exploiting Data Missingness in Bayesian Network Modeling
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UAI
2000
15 years 1 months ago
Being Bayesian about Network Structure
In many domains, we are interested in analyzing the structure of the underlying distribution, e.g., whether one variable is a direct parent of the other. Bayesian model selection a...
Nir Friedman, Daphne Koller
128
Voted
JCB
2007
198views more  JCB 2007»
15 years 14 days ago
Bayesian Hierarchical Model for Large-Scale Covariance Matrix Estimation
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
Dongxiao Zhu, Alfred O. Hero III
IJSNET
2007
155views more  IJSNET 2007»
15 years 15 days ago
Distributed Bayesian fault diagnosis of jump Markov systems in wireless sensor networks
: A Bayesian distributed online change detection algorithm is proposed for monitoring a dynamical system by a wireless sensor network. The proposed solution relies on modelling the...
Hichem Snoussi, Cédric Richard
105
Voted
ICASSP
2009
IEEE
14 years 10 months ago
Spoken language interpretation: On the use of dynamic Bayesian networks for semantic composition
In the context of spoken language interpretation, this paper introduces a stochastic approach to infer and compose semantic structures. Semantic frame structures are directly deri...
Marie-Jean Meurs, Fabrice Lefevre, Renato de Mori
103
Voted
ICANN
2009
Springer
15 years 4 months ago
Efficient Uncertainty Propagation for Reinforcement Learning with Limited Data
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
Alexander Hans, Steffen Udluft