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SUMMARY:Mixture Models and the EM Algorithm - Professor Chris Bishop\, Mic
 rosoft Research Cambridge
DTSTART:20061005T150000Z
DTEND:20061005T170000Z
UID:TALK5539@talks.cam.ac.uk
CONTACT:Zoubin Ghahramani
DESCRIPTION:In this tutorial I will give an introduction to the Gaussian m
 ixture model\, and the use of the EM (expectation-maximization) algorithm 
 to determine its parameters by maximizing the likelihood function. As well
  as being of widespread practical importance\, these techniques will sever
  to introduce some key concepts in machine learning such as latent variabl
 es. 
LOCATION:LR4\, Engineering\, Department of
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