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IJCNN
2000
IEEE
14 years 1 days ago
On MCMC Sampling in Bayesian MLP Neural Networks
Bayesian MLP neural networks are a flexible tool in complex nonlinear problems. The approach is complicated by need to evaluate integrals over high-dimensional probability distri...
Aki Vehtari, Simo Särkkä, Jouko Lampinen
NIPS
2000
13 years 9 months ago
Active Learning for Parameter Estimation in Bayesian Networks
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
Simon Tong, Daphne Koller
IJAR
2006
118views more  IJAR 2006»
13 years 7 months ago
Learning Bayesian network parameters under order constraints
We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...
A. J. Feelders, Linda C. van der Gaag
WWW
2007
ACM
14 years 8 months ago
Bayesian network based sentence retrieval model
This paper makes an intensive investigation of the application of Bayesian network in sentence retrieval and introduces three Bayesian network based sentence retrieval models with...
Keke Cai, Jiajun Bu, Chun Chen, Kangmiao Liu, Wei ...
SAC
2010
ACM
14 years 2 months ago
Applying taxonomic knowledge to Bayesian belief network for personalized search
Keyword-based search returns its results without concern for the information needs of users at a particular time. In general, search queries are too short to represent what users ...
Jae-won Lee, Han-joon Kim, Sang-goo Lee