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FLAIRS
2004
13 years 11 months ago
Computing Marginals with Hierarchical Acyclic Hypergraphs
How to compute marginals efficiently is one of major concerned problems in probabilistic reasoning systems. Traditional graphical models do not preserve all conditional independen...
S. K. Michael Wong, Tao Lin
ICML
2005
IEEE
14 years 10 months ago
Hierarchic Bayesian models for kernel learning
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance w...
Mark Girolami, Simon Rogers
ACL
2006
13 years 11 months ago
A Hierarchical Bayesian Language Model Based On Pitman-Yor Processes
We propose a new hierarchical Bayesian n-gram model of natural languages. Our model makes use of a generalization of the commonly used Dirichlet distributions called Pitman-Yor pr...
Yee Whye Teh
COGSCI
2006
75views more  COGSCI 2006»
13 years 9 months ago
A Hierarchical Bayesian Model of Human Decision-Making on an Optimal Stopping Problem
We consider human performance on an optimal stopping problem where people are presented with a list of numbers independently chosen from a uniform distribution. People are told ho...
Michael D. Lee
ICIP
2010
IEEE
13 years 7 months ago
Bayesian regularization of diffusion tensor images using hierarchical MCMC and loopy belief propagation
Based on the theory of Markov Random Fields, a Bayesian regularization model for diffusion tensor images (DTI) is proposed in this paper. The low-degree parameterization of diffus...
Siming Wei, Jing Hua, Jiajun Bu, Chun Chen, Yizhou...