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» On Fitting Mixture Models
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PAMI
1998
94views more  PAMI 1998»
13 years 7 months ago
Bayesian Approaches to Gaussian Mixture Modeling
—A Bayesian-based methodology is presented which automatically penalizes overcomplex models being fitted to unknown data. We show that, with a Gaussian mixture model, the approac...
Stephen J. Roberts, Dirk Husmeier, Iead Rezek, Wil...
GECCO
2004
Springer
143views Optimization» more  GECCO 2004»
14 years 28 days ago
Efficient Clustering-Based Genetic Algorithms in Chemical Kinetic Modelling
Two efficient clustering-based genetic algorithms are developed for the optimisation of reaction rate parameters in chemical kinetic modelling. The genetic algorithms employed are ...
Lionel Elliott, Derek B. Ingham, Adrian G. Kyne, N...
BMCBI
2008
82views more  BMCBI 2008»
13 years 7 months ago
Envelope: interactive software for modeling and fitting complex isotope distributions
Background: An important aspect of proteomic mass spectrometry involves quantifying and interpreting the isotope distributions arising from mixtures of macromolecules with differe...
Michael T. Sykes, James R. Williamson
CVPR
2006
IEEE
14 years 9 months ago
Body Localization in Still Images Using Hierarchical Models and Hybrid Search
We present a 3-level hierarchical model for localizing human bodies in still images from arbitrary viewpoints. We first fit a simple tree-structured model defined on a small landm...
Jiayong Zhang, Jiebo Luo, Robert T. Collins, Yanxi...
SADM
2010
141views more  SADM 2010»
13 years 2 months ago
A parametric mixture model for clustering multivariate binary data
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman