A tutorial on learning with Bayesian networks

A tutorial on learning with Bayesian networks (1995)

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by David Heckerman

Venue:	Learning in Graphical Models
Citations:	711 - 4 self

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@TECHREPORT{Heckerman95atutorial,
    author = {David Heckerman},
    title = {A tutorial on learning with Bayesian networks},
    institution = {Learning in Graphical Models},
    year = {1995}
}

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Abstract

A companion set of lecture slides is available at

Citations

6234	Maximum likelihood from incomplete data via the EM algorithm - Dempster, Laird, et al. - 1977
3011	Stochastic Relaxation, Gibbs Distributions and the Bayesian Restoration of Images - Geman, Geman - 1984
1583	Estimating the dimension of a model - Schwarz - 1978
1572	BW: Density Estimation for Statistics and Data Analysis - Silverman - 1986
1080	Local computations with probabilities on graphical structures and their application to expert systems (with discussion - Lauritzen, Spiegelhalter - 1988
1015	The Foundations of Statistics - Savage - 1954
876	A Bayesian method for the induction of probabilistic networks from data - Cooper, Herskovits - 1992
786	Bayesian Theory - Bernardo, Smith - 1994
751	Learning Bayesian networks: the combination of knowledge and statistical data - Heckerman, Geiger, et al. - 1995
719	FV: An Introduction to Bayesian Networks - Jensen - 1996
718	Bayes factors - Kass, Raftery - 1995
639	Exploratory Data Analysis - Tukey - 1977
616	Judgment under uncertainty: heuristics and biases - Tversky, Kahneman - 1974
496	The computational complexity of probabilistic inference using Bayesian belief networks - Cooper - 1990
448	Probabilistic inference using Markov chain Monte Carlo methods - Neal - 1993
426	D.: Markov chain Monte Carlo in practice - Gilks, Richardson, et al. - 1996
419	Probability and Statistics - DeGroot, Schervish
417	Bayesian interpolation - MacKay - 1992
383	Causation, prediction, and search - Spirtes, Glymour, et al. - 2000
353	Graphical Models in Applied Multivariate Statistics - Whittaker - 1990
346	A practical Bayesian framework for backpropagation networks.Neural computation - MacKay
298	Fusion, propagation, and structuring in belief networks - Pearl - 1986
293	Influence diagrams - Howard, Matheson - 2005
231	Marginal likelihood from the Gibbs output - Chib - 1995
220	Approximating probabilistic inference in Bayesian belief networks is NP-hard - Dagum, Luby - 1993
213	Model selection and accounting for model uncertainty in graphical models using Occam’s window - Madigan, Raftery - 1994
201	The ALARM monitoring system: A case study with two probabilistic inference techniques for belief networks - Beinlich, Suermondt, et al. - 1989
178	Equivalence and synthesis of causal models - Verma, Pearl - 1990
177	Bayesian model selection in social research (with discussion by gelman - Raftery - 1995
176	Bayesian analysis in expert systems - Spiegelhalter, Dawid, et al. - 1993
176	Sequential updating of conditional probabilities on directed graphical structures - Spiegelhalter, Lauritzen - 1990
175	TS: A theory of inferred causation - Pearl, Verma
165	Bayesian graphical models for discrete data - Madigan, York - 1995
155	Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables - Chickering, Heckerman - 1997
139	Truth and probability - Ramsey - 1931
132	Causal diagrams for empirical research - Pearl - 1994
131	Statistical Theory: The Prequential Approach - Dawid - 1984
131	Bayesian updating in recursive graphical models by local computations - Jensen, Lauritzen, et al. - 1989
125	Propagation of probabilities, means, variances in mixed graphical association models - Lauritzen - 1992
120	Probability, frequency and reasonable expectation - Cox - 1946
114	An algebra of bayesian belief universes for knowledge based systems, Networks 20 - Jensen, Olesen, et al. - 1990
110	Learning Equivalence Classes of Bayesian Network Structure - Chickering - 1996
88	Theory of Probability - DeFinetti - 1975
83	Improving the convergence of back-propagation learning with second order methods - Becker, LeCun - 1989
83	The chain graph Markov property - Frydenberg - 1990
78	Probability and The Weighing of Evidence - Good - 1950
76	Applications of a general propagation algorithm for probabilistic expert systems - Dawid - 1992
73	A transformational characterization of equivalent Bayesian network structures - Chickering - 1995
68	Local learning in probabilistic networks with hidden variables - Russell, Binder, et al. - 1995
60	BUGS: A program to perform Bayesian inference using Gibbs sampling - Thomas, Spiegelhalter, et al.