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SUMMARY:Divergence measures and latent variable models - Ulrich Paquet
DTSTART:20060719T130000Z
DTEND:20060719T140000Z
UID:TALK5135@talks.cam.ac.uk
CONTACT:Ryan Prescott Adams
DESCRIPTION:Alpha-divergences have attracted recent attention as a measure
  of divergence for generalizing algorithms for approximate inference (like
  Variational Bayes and Expectation Propagation) into a unified framework. 
 This talk explores the use and effect of such divergence measures under mu
 tivariate mixtures of Gaussians\, an example of a simple non-trivial laten
 t variable model. In particular\, symmetry-breaking\, Ockam-hills for diff
 erent measures of divergence\, behaviour under multiple modes\, and practi
 cal results are discussed.
LOCATION:HEP Seminar Room\, Cavendish Laboratory
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