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ICCV
2009
IEEE
15 years 2 months ago
Deformable Model Fitting with a Mixture of Local Experts
Local experts have been used to great effect for fitting deformable models to images. Typically, the best location in an image for the deformable model’s landmarks are found t...
Jason M. Saragih, Simon Lucey, Jeffrey F. Cohn
ICCV
2005
IEEE
14 years 3 months ago
Bayesian Body Localization Using Mixture of Nonlinear Shape Models
We present a 2D model-based approach to localizing human body in images viewed from arbitrary and unknown angles. The central component is a statistical shape representation of th...
Jiayong Zhang, Robert T. Collins, Yanxi Liu
ICIP
2009
IEEE
13 years 7 months ago
Random swap EM algorithm for finite mixture models in image segmentation
The Expectation-Maximization (EM) algorithm is a popular tool in statistical estimation problems involving incomplete data or in problems which can be posed in a similar form, suc...
Qinpei Zhao, Ville Hautamäki, Ismo Kärkk...
GECCO
2011
Springer
236views Optimization» more  GECCO 2011»
13 years 1 months ago
Online, GA based mixture of experts: a probabilistic model of ucs
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs
NAACL
1994
13 years 11 months ago
Language Modeling with Sentence-Level Mixtures
Thispaperintroduces a simple mixtare languagemodelthat attempts to capture long distance conslraints in a sentence orparagraph. The model is an m-component mixture of Irigram mode...
Rukmini Iyer, Mari Ostendorf, Jan Robin Rohlicek