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» A Model for Structural Changes of Belief
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UAI
2004
14 years 11 months ago
Dependent Dirichlet Priors and Optimal Linear Estimators for Belief Net Parameters
A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
Peter Hooper
EGOV
2003
Springer
15 years 2 months ago
Structuring Dialogue between the People and Their Representatives
Conversations between citizens and their representatives may take a number of forms. In this paper, we consider one of these — letters between citizens and representatives — an...
Katie Greenwood, Trevor J. M. Bench-Capon, Peter M...
ICML
2007
IEEE
15 years 10 months ago
Incremental Bayesian networks for structure prediction
We propose a class of graphical models appropriate for structure prediction problems where the model structure is a function of the output structure. Incremental Sigmoid Belief Ne...
Ivan Titov, James Henderson
JMLR
2010
169views more  JMLR 2010»
14 years 4 months ago
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images
Deep belief nets have been successful in modeling handwritten characters, but it has proved more difficult to apply them to real images. The problem lies in the restricted Boltzma...
Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E....
CSDA
2007
100views more  CSDA 2007»
14 years 9 months ago
Estimation in a linear multivariate measurement error model with a change point in the data
A linear multivariate measurement error model AX = B is considered. The errors in A B are row-wise finite dependent, and within each row, the errors may be correlated. Some of th...
Alexander Kukush, Ivan Markovsky, Sabine Van Huffe...