PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Induced Graph Semantics: Another look at the Hammersley-Clifford theorem
Tim Sears and Peter Sunehag
In: 27th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering AIP Conference Proceedings , 954 . (2007) American Institute of Physics , Saratoga Springs, NY , pp. 125-132. ISBN 978-0-7354-0468-7

Abstract

The Hammersley-Clifford (H-C) theorem relates the factorization properties of a probability distribution to the clique structure of an undirected graph. If a density factorizes according to the clique structure of an undirected graph, the theorem guarantees that the distribution satisfies the Markov property and vice versa. We show how to generalize the H-C theorem to different notions of decomposability and the corresponding generalized-Markov property. Finally we discuss how our technique might be used to arrive at other generalizations of the H-C theorem, inducing a graph semantics adapted to the modeling problem.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:4048
Deposited By:S V N Vishwanathan
Deposited On:25 February 2008