
heckermacOJmicrosoft.com
– Dan Geiger, David Heckerman, Christopher Meek

172

A Guide to the Literature on Learning Probabilistic Networks From Data
– Wray Buntine
 1996

79

A Bayesian Approach to Causal Discovery
– David Heckerman, Christopher Meek, Gregory Cooper
 1997

178

Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables
– David Maxwell Chickering, David Heckerman
 1997


unknown title
– Learning Bayesian


heckerma(~.microsoft.com
– Dan Geiger, David Heckerman, Christopher Meek

564

Dynamic Bayesian Networks: Representation, Inference and Learning
– Kevin Patrick Murphy
 2002

849

A tutorial on learning with Bayesian networks
– David Heckerman
 1995

913

Learning Bayesian networks: The combination of knowledge and statistical data
– David Heckerman, David M. Chickering
 1995

130

Learning Bayesian Networks is NPHard
– David Chickering, Dan Geiger, David Heckerman
 1994

8

Challenge: Where is the Impact of Bayesian Networks in Learning?
– Nir Friedman, Moises Goldszmidt, David Heckerman
 1997

9

Computationally efficient methods for selecting among mixtures of graphical models
– B. Thiesson, C. Meek, D. M. Chickering, D. Heckerman
 1999

25

Learning mixtures of DAG models
– Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman
 1997

1

A Statistical Perspective on Data Mining
– Ranjan Maitra

21

Learning Mixtures of Bayesian Networks
– Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman
 1997

19

Learning Causal Networks from Data: A survey and a new algorithm for recovering possibilistic causal networks
– Ramon Sangüesa, Ulises Cortés
 1997

587

Bayesian Network Classifiers
– Nir Friedman, Dan Geiger, Moises Goldszmidt
 1997

35

Learning Bayesian Networks from Data: An Efficient Approach Based on Information Theory
– Jie Cheng, David Bell, Weiru Liu
 1997

93

Learning Bayesian Networks from Data: An InformationTheory Based Approach
– Jie Cheng, Russell Greiner, Jonathan Kelly, David Bell, Weiru Liu
