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» Compiling relational Bayesian networks for exact inference
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WWW
2005
ACM
14 years 8 months ago
Association search in semantic web: search + inference
Association search is to search for certain instances in semantic web and then make inferences from and about the instances we have found. In this paper, we propose the problem of...
Bangyong Liang, Jie Tang, Juan-Zi Li
JMLR
2010
125views more  JMLR 2010»
13 years 2 months ago
Continuous Time Bayesian Network Reasoning and Learning Engine
We present a continuous time Bayesian network reasoning and learning engine (CTBN-RLE). A continuous time Bayesian network (CTBN) provides a compact (factored) description of a co...
Christian R. Shelton, Yu Fan, William Lam, Joon Le...
NIPS
1998
13 years 8 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
KDD
2005
ACM
103views Data Mining» more  KDD 2005»
14 years 7 months ago
Fast discovery of unexpected patterns in data, relative to a Bayesian network
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
Szymon Jaroszewicz, Tobias Scheffer
IJAR
2006
98views more  IJAR 2006»
13 years 7 months ago
Inference in hybrid Bayesian networks with mixtures of truncated exponentials
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for solving hybrid Bayesian networks. Any probability density function can be approximated...
Barry R. Cobb, Prakash P. Shenoy