Learning with Mixtures of Trees (1999)


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by Marina Meila-Predoviciu
Citations:17 - 0 self

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9 Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains – Helge Langseth, Thomas D. Nielsen, Richard Dybowski - 2003
109 Learning with mixtures of trees – Marina Meilă, Michael I. Jordan - 2000
9 Exploiting parameter domain knowledge for learning in Bayesian networks – Radu Stefan Niculescu - 2005
3 Fast Factored Density Estimation and Compression with Bayesian Networks – Scott Davies, John Lafferty - 2002
67 Graphical models and automatic speech recognition – Jeffrey A. Bilmes - 2003
564 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
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2 Bayesian Networks for Genomic Analysis – Paola Sebastiani, Maria M. Abad, Marco F. Ramoni - 2004
587 Bayesian Network Classifiers – Nir Friedman, Dan Geiger, Moises Goldszmidt - 1997
Recognition The Graphical Models Team – Jhu Summer Workshop, Jeff A. Bilmes, Geoff Zweig Ibm, Karen Livescu Mit, Peng Xu, Kirk Jackson Dod, Yigal Br, Man Phonetact Inc, Eric S, Ness Speechworks, Eva Holtz, Bill Byrne, Jhu Summer Workshop, Geoff Zweig Ibm, Peng Xu, Kirk Jackson Dod, Yigal Br, Man Phonetact Inc, Eric S, Ness Speechworks, Eva Holtz, Bill Byrne Johns - 2001
7 Bayesian Networks with Applications in Reliability Analysis – Helge Langseth - 2002
93 Learning Bayesian Networks from Data: An Information-Theory Based Approach – Jie Cheng, Russell Greiner, Jonathan Kelly, David Bell, Weiru Liu
172 A Guide to the Literature on Learning Probabilistic Networks From Data – Wray Buntine - 1996
1 Bethe Free Energy and Contrastive Divergence Approximations for Undirected Graphical Models – Yee Whye Teh, Yee Whye Teh - 2003
c ○ 2001 Kluwer Academic Publishers. Manufactured in The Netherlands. Robust Learning with Missing Data – Marco Ramoni, Paola Sebastiani, Pat Langley
849 A tutorial on learning with Bayesian networks – David Heckerman - 1995
36 Tractable Bayesian Learning of Tree Belief Networks – Marina Meila, Tommi Jaakkola - 2000
5 Learning possibilistic graphical models from data – Christian Borgelt, Rudolf Kruse - 2003
14 Theory refinement of bayesian networks with hidden variables – Sowmya Ramachandran - 1998