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SUMMARY:Markov Random Fields for Classification in High Dimensional Spaces
  with Application to fMRI Analysis - Dr Avishay Carmi\, CUED
DTSTART:20081210T141500Z
DTEND:20081210T151500Z
UID:TALK15467@talks.cam.ac.uk
CONTACT:Rachel Fogg
DESCRIPTION:In this talk we present a new classification algorithm\nfor hi
 gh dimensional problems. The algorithm uses a Markov random field for mode
 ling meaningful interactions within the training data set. The model param
 eters are efficiently estimated using the Kalman filter algorithm and adap
 ted to fit the test data using a recursive matrix formulation of the exten
 ded Baum-Welch algorithm. A spatially likelihood test procedure is then us
 ed for classifying the data. The\nperformance of the new algorithm is demo
 nstrated in fMRI classification.\n
LOCATION:LR12\, Engineering\, Department of
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