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SSPR
2010
Springer
13 years 6 months ago
Non-parametric Mixture Models for Clustering
Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM),...
Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain
CSDA
2007
110views more  CSDA 2007»
13 years 7 months ago
Bayesian modelling strategies for spatially varying regression coefficients: A multivariate perspective for multiple outcomes
This paper considers modelling spatially varying regression effects for multivariate mortality count outcomes. Alternative approaches to spatial regression heterogeneity are consi...
P. Congdon
ICPR
2000
IEEE
13 years 11 months ago
A Bayesian Approach to Object Identification in Pattern Recognition
We present a new Bayesian approach to object identification: variants. By object identification we mean the detection of the member (regular variant) of a given statistical popula...
Gunter Ritter, María Teresa Gallegos
JMLR
2010
150views more  JMLR 2010»
13 years 2 months ago
Supervised Dimension Reduction Using Bayesian Mixture Modeling
We develop a Bayesian framework for supervised dimension reduction using a flexible nonparametric Bayesian mixture modeling approach. Our method retrieves the dimension reduction ...
Kai Mao, Feng Liang, Sayan Mukherjee
TASLP
2010
97views more  TASLP 2010»
13 years 2 months ago
Hierarchical Bayesian Language Models for Conversational Speech Recognition
Traditional n-gram language models are widely used in state-of-the-art large vocabulary speech recognition systems. This simple model suffers from some limitations, such as overfi...
Songfang Huang, Steve Renals