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    <title>Physics : arXiv</title>
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    <description>Mostrando recursos 1 - 1 de 1</description>
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    <title>Universia-Recursos de Aprendizaje</title>
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  <item rdf:about="http://biblioteca.universia.net/ficha.do?id=184839">
    <title>A Geometric Formulation of Occam's Razor for Inference of Parametric
  Distributions</title>
    <link>http://biblioteca.universia.net/ficha.do?id=184839</link>
    <description>I define a natural measure of the complexity of a parametric distribution
relative to a given true distribution called the {\it razor} of a model family.
The Minimum Description Length principle (MDL) and Bayesian inference are shown
to give empirical approximations of the razor via an analysis that
significantly extends existing results on the asymptotics of Bayesian model
selection. I treat parametric families as manifolds embedded in the space of
distributions and derive a canonical metric...</description>
    <dc:creator>Balasubramanian, Vijay</dc:creator>
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