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UAI
2004
15 years 6 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
ICASSP
2011
IEEE
14 years 8 months ago
A-Functions: A generalization of Extended Baum-Welch transformations to convex optimization
We introduce the Line Search A-Function (LSAF) technique that generalizes the Extended-Baum Welch technique in order to provide an effective optimization technique for a broader s...
Dimitri Kanevsky, David Nahamoo, Tara N. Sainath, ...
AAAI
1998
15 years 6 months ago
Probabilistic Frame-Based Systems
Two of the most important threads of work in knowledge representation today are frame-based representation systems (FRS's) and Bayesian networks (BNs). FRS's provide an ...
Daphne Koller, Avi Pfeffer
SAC
2009
ACM
15 years 11 months ago
Applying latent dirichlet allocation to group discovery in large graphs
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
Keith Henderson, Tina Eliassi-Rad
EDM
2008
127views Data Mining» more  EDM 2008»
15 years 6 months ago
Adaptive Test Design with a Naive Bayes Framework
Bayesian graphical models are commonly used to build student models from data. A number of standard algorithms are available to train Bayesian models from student skills assessment...
Michel C. Desmarais, Alejandro Villarreal, Michel ...