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From "Edward J. Yoon (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HAMA-675) Deep Learning Computation Model
Date Wed, 16 Jul 2014 10:40:04 GMT

    [ https://issues.apache.org/jira/browse/HAMA-675?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14063370#comment-14063370
] 

Edward J. Yoon commented on HAMA-675:
-------------------------------------

I think, it'd be nice if we add a Google's DistBelief clone project as a new module like Graph
package.

> Deep Learning Computation Model
> -------------------------------
>
>                 Key: HAMA-675
>                 URL: https://issues.apache.org/jira/browse/HAMA-675
>             Project: Hama
>          Issue Type: New Feature
>          Components: machine learning
>            Reporter: Thomas Jungblut
>
> Jeff Dean mentioned a computational model in this video: http://techtalks.tv/talks/57639/
> There they are using the same idea of the Pregel system, they are defining a upstream
and a downstream computation function for a neuron (for cost and its gradient). Then you can
roughly tell about how the framework should partition the neurons.
> All the messaging will be handled by the underlying messaging framework.
> Can we implement something equally?



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