|
486
|
Approximating discrete probability distributions with dependence trees
– C. I<. Chow, Sexior Member, C. N. Liu
- 1968
|
|
6234
|
Maximum likelihood from incomplete data via the EM algorithm
– A. P. Dempster, N. M. Laird, D. B. Rubin
- 1977
|
|
5667
|
Probabilistic reasoning in intelligent systems
– Judea Pearl
- 1988
|
|
752
|
Learning Bayesian networks: The combination of knowledge and statistical data
– David Heckerman, David M. Chickering
- 1995
|
|
7324
|
Cache-oblivious algorithms
– M FRIGO, C E LEISERSON, H PROKOP, S RAMACHANDRAN
- 1999
|
|
155
|
Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables
– David Maxwell Chickering, David Heckerman
- 1997
|
|
451
|
Bayesian Network Classifiers
– Nir Friedman, Dan Geiger, Moises Goldszmidt
- 1997
|
|
31
|
Learning polytrees
– Sanjoy Dasgupta
- 1999
|
|
189
|
The Bayesian Structural EM Algorithm
– Nir Friedman
- 1998
|
|
416
|
Bayesian Classification (AutoClass): Theory and Results
– P Cheeseman, J Stutz
- 1996
|
|
719
|
FV: An Introduction to Bayesian Networks
– Jensen
- 1996
|
|
1581
|
Estimating the dimension of a model
– G E Schwarz
- 1978
|
|
848
|
a . The melanocyte model
– M ALA W ISTA, S
- 1971
|
|
615
|
Introduction to Graph Theory
– D West
- 2001
|
|
179
|
The EM algorithm for graphical association models with missing data
– S L Lauritzen
- 1995
|
|
28
|
An entropy-based learning algorithm of Bayesian conditional trees
– D Geiger
|
|
500
|
Probabilistic Networks and Expert Systems
– R Cowell, A Dawid, S Lauritzen, D Spiegelhalter
- 1999
|
|
108
|
Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets
– Andrew Moore, Mary Soon Lee
- 1997
|
|
3012
|
Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
– S Geman, D Geman
- 1984
|
