Title:
Graphical Models for the Internet
Graphical Models for the Internet
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Author(s)
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.
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Date Issued
2011-04-29
Extent
61:42 minutes
Resource Type
Moving Image
Resource Subtype
Lecture