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» Hierarchical mixture models: a probabilistic analysis
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JMLR
2010
156views more  JMLR 2010»
13 years 2 months ago
Classification with Incomplete Data Using Dirichlet Process Priors
A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...
Chunping Wang, Xuejun Liao, Lawrence Carin, David ...
BMCBI
2006
131views more  BMCBI 2006»
13 years 7 months ago
Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to life span
Background: The statistical modeling of biomedical corpora could yield integrated, coarse-to-fine views of biological phenomena that complement discoveries made from analysis of m...
David M. Blei, K. Franks, Michael I. Jordan, I. Sa...
NIPS
2004
13 years 9 months ago
A Three Tiered Approach for Articulated Object Action Modeling and Recognition
Visual action recognition is an important problem in computer vision. In this paper, we propose a new method to probabilistically model and recognize actions of articulated object...
Le Lu, Gregory D. Hager, Laurent Younes
PAMI
2007
155views more  PAMI 2007»
13 years 7 months ago
Localization of Shapes Using Statistical Models and Stochastic Optimization
—In this paper, we present a new model for deformations of shapes. A pseudolikelihood is based on the statistical distribution of the gradient vector field of the gray level. The...
François Destrempes, Max Mignotte, Jean-Fra...
WABI
2009
Springer
155views Bioinformatics» more  WABI 2009»
14 years 2 months ago
A Markov Classification Model for Metabolic Pathways
Background: This paper considers the problem of identifying pathways through metabolic networks that relate to a specific biological response. Our proposed model, HME3M, first ide...
Timothy Hancock, Hiroshi Mamitsuka