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PAMI
2006
215views more  PAMI 2006»
14 years 9 months ago
Bayesian Feature and Model Selection for Gaussian Mixture Models
We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of ...
Constantinos Constantinopoulos, Michalis K. Titsia...
NIPS
1992
14 years 11 months ago
Hidden Markov Model} Induction by Bayesian Model Merging
This paper describes a technique for learning both the number of states and the topologyof Hidden Markov Models from examples. The inductionprocess starts with the most specific m...
Andreas Stolcke, Stephen M. Omohundro
CSDA
2010
91views more  CSDA 2010»
14 years 10 months ago
Default Bayesian model determination methods for generalised linear mixed models
In this paper, we consider a default strategy for fully Bayesian model determination for GLMMs. We address the two key issues of default prior specification and computation. In pa...
Antony M. Overstall, Jonathan J. Forster
JAIR
2008
93views more  JAIR 2008»
14 years 9 months ago
A Rigorously Bayesian Beam Model and an Adaptive Full Scan Model for Range Finders in Dynamic Environments
This paper proposes and experimentally validates a Bayesian network model of a range finder adapted to dynamic environments. All modeling assumptions are rigorously explained, and...
Tinne De Laet, Joris De Schutter, Herman Bruyninck...
CSDA
2008
117views more  CSDA 2008»
14 years 10 months ago
Parametric and nonparametric Bayesian model specification: A case study involving models for count data
In this paper we present the results of a simulation study to explore the ability of Bayesian parametric and nonparametric models to provide an adequate fit to count data, of the t...
Milovan Krnjajic, Athanasios Kottas, David Draper