Dependency networks for inference, collaborative filtering, and data visualization

by David Heckerman , David Maxwell Chickering , Christopher Meek , Robert Rounthwaite , Carl Kadie
Venue:Journal of Machine Learning Research
Citations:159 - 10 self

Active Bibliography

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12 Population Markov Chain Monte Carlo – Kathryn Blackmond Laskey, James Myers - 2003
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41 Rule-based Evolutionary Online Learning Systems: LEARNING BOUNDS, CLASSIFICATION, AND PREDICTION – Martin V. Butz - 2004
Automated Global . . . For Effective Local Building Block Processing in XCS – Martin V. Butz, Martin Pelikan, Xavier Llorà, David E. Goldberg - 2005
22 Parallel estimation of distribution algorithms – Jiří Očenášek - 2002
1 Doctoral Thesis – Supervisor Ing, Josef Schwarz, Jiří Očenášek - 2002
3 Learning Bayesian Networks for Solving Real-World Problems – Moninder Singh - 1998
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3 A Bayesian Local Causal Discovery Framework – Subramani Mani - 2005
7 A Bayesian network classification methodology for gene expression data – Paul Helman, Robert Veroff, Susan R. Atlas, Cheryl Willman - 2004
37 Improved learning of Bayesian networks – Robert Castelo, Craig Boutilier - 2001
167 Probabilistic independence networks for hidden Markov probability models – Padhraic Smyth, David Heckerman, Michael I. Jordan - 1996
Scalable Pseudo-Likelihood Estimation in Hybrid Random Fields – Antonino Freno, Edmondo Trentin, Marco Gori
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7 Prior Information and Generalized Questions – Jörg C. Lemm - 1996
Bayesian Modelling in Machine Learning: A Tutorial Review – Matthias Seeger - 2009