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ACL
2006
14 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
PR
2011
14 years 4 months ago
A variational Bayesian methodology for hidden Markov models utilizing Student's-t mixtures
The Student’s-t hidden Markov model (SHMM) has been recently proposed as a robust to outliers form of conventional continuous density hidden Markov models, trained by means of t...
Sotirios Chatzis, Dimitrios I. Kosmopoulos
JMLR
2011
148views more  JMLR 2011»
14 years 4 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan
CVPR
2008
IEEE
15 years 12 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
AI
2005
Springer
14 years 9 months ago
Bayesian network modelling through qualitative patterns
In designing a Bayesian network for an actual problem, developers need to bridge the gap between ematical abstractions offered by the Bayesian-network formalism and the features o...
Peter J. F. Lucas