Embedded Bayesian Network Classifiers (1997)

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by David Heckerman , Christopher Meek
Citations:8 - 1 self

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155 Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables – David Maxwell Chickering, David Heckerman - 1997
41 Stratified Exponential Families: Graphical Models and Model Selection – Dan Geiger, David Heckerman, Henry King, Christopher Meek, Redmond Wa - 1998
20 Models and Selection Criteria for Regression and Classification – David Heckerman, Christopher Meek - 1997
37 Asymptotic model selection for directed networks with hidden variables – Dan Geiger, David Heckerman, Christopher Meek - 1996
27 Learning Probabilistic Networks – Paul J Krause - 1998
122 Dependency networks for inference, collaborative filtering, and data visualization – David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Kadie
33 Bayesian Model Selection and Model Averaging – Larry Wasserman - 1999
3 Generalizing The Derivation Of The Schwarz Information Criterion – Joseph E. Cavanaugh, Andrew A. Neath - 1999
16 Learning Mixtures of Bayesian Networks – Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman - 1997
25 The variable selection problem – Edward I. George - 2000
16 Graphical Models and Exponential Families – Dan Geiger, Christopher Meek - 1998
393 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
4 Supervised Learning of Bayesian Network Parameters Made Easy – Hannes Wettig, Peter Grünwald, Teemu Roos, Petri Myllymäki, Henry Tirri - 2002
11 On Discriminative Bayesian Network Classifiers and Logistic Regression – Teemu Roos, Hannes Wettig, Peter Grünwald, Petri Myllymäki, Henry Tirri, Pedro Larrañaga, Jose A. Lozano, Jose M. Peña, Iñaki Inza - 2005
1 Tree Augmented Classification of Binary Data Minimizing Stochastic Complexity – Mats Gyllenberg, Timo Koski - 2002
3 A Bayesian Local Causal Discovery Framework – Subramani Mani - 2005
214 Operations for Learning with Graphical Models – Wray L. Buntine - 1994
161 Learning the structure of dynamic probabilistic networks – Nir Friedman, Kevin Murphy, Stuart Russell - 1998
3 Fast Factored Density Estimation and Compression with Bayesian Networks – Scott Davies, John Lafferty - 2002