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JMLR
2012
11 years 10 months ago
Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying as...
Marco Grzegorczyk, Dirk Husmeier
SIGIR
2009
ACM
14 years 2 months ago
A bayesian learning approach to promoting diversity in ranking for biomedical information retrieval
In this paper, we propose a Bayesian learning approach to promoting diversity for information retrieval in biomedicine and a re-ranking model to improve retrieval performance in t...
Xiangji Huang, Qinmin Hu
UAI
2003
13 years 9 months ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
IJAR
2007
130views more  IJAR 2007»
13 years 7 months ago
Bayesian network learning algorithms using structural restrictions
The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domai...
Luis M. de Campos, Javier Gomez Castellano
AI
2002
Springer
13 years 7 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...