W. Buntine. Journal of Artificial Intelligence Research, (1994)
Zusammenfassung
This paper is a multidisciplinary review of empirical, statistical learning from a graphical
model perspective. Well-known examples of graphical models include Bayesian networks,
directed graphs representing a Markov chain, and undirected networks representing
a Markov field. These graphical models are extended to model data analysis and empirical
learning using the notation of plates. Graphical operations for simplifying and manipulating
a problem are provided including decomposition,...
%0 Journal Article
%1 citeulike:562662
%A Buntine, Wray L.
%D 1994
%J Journal of Artificial Intelligence Research
%K bayesian graphical learning ml model proj:o4p toread
%P 159--225
%T Operations for Learning with Graphical Models
%U http://citeseer.ist.psu.edu/6938.html
%V 2
%X This paper is a multidisciplinary review of empirical, statistical learning from a graphical
model perspective. Well-known examples of graphical models include Bayesian networks,
directed graphs representing a Markov chain, and undirected networks representing
a Markov field. These graphical models are extended to model data analysis and empirical
learning using the notation of plates. Graphical operations for simplifying and manipulating
a problem are provided including decomposition,...
@article{citeulike:562662,
abstract = {This paper is a multidisciplinary review of empirical, statistical learning from a graphical
model perspective. Well-known examples of graphical models include Bayesian networks,
directed graphs representing a Markov chain, and undirected networks representing
a Markov field. These graphical models are extended to model data analysis and empirical
learning using the notation of plates. Graphical operations for simplifying and manipulating
a problem are provided including decomposition,...},
added-at = {2007-08-15T11:46:37.000+0200},
author = {Buntine, Wray L.},
biburl = {https://www.bibsonomy.org/bibtex/28952cf0d215116e038971f7c30d6d19d/wnpxrz},
citeulike-article-id = {562662},
interhash = {c7dd650780467c934551356630a7b739},
intrahash = {8952cf0d215116e038971f7c30d6d19d},
journal = {Journal of Artificial Intelligence Research},
keywords = {bayesian graphical learning ml model proj:o4p toread},
pages = {159--225},
priority = {0},
timestamp = {2008-01-12T12:00:47.000+0100},
title = {Operations for Learning with Graphical Models},
url = {http://citeseer.ist.psu.edu/6938.html},
volume = 2,
year = 1994
}