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    Graphical Models for the Internet

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    transcription.txt (53.34Kb)
    Date
    2011-04-29
    Author
    Smola, Alexander
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    Abstract
    In this talk I will present algorithms for performing large scale inference using Latent Dirichlet Allocation and a novel Cluster-Topic model to estimate user preferences and to group stories into coherent, topically consistent storylines. I will discuss both the statistical modeling challenges involved and the very large scale implementation of such models which allows us to perform estimation on over 50 million users on a Hadoop cluster.
    URI
    http://hdl.handle.net/1853/39019
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    • Computational Science and Engineering Seminar Series [35]

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