Cool example - thanks Nick!

2013/2/4 Robert Kern <[email protected]>:
> On Mon, Feb 4, 2013 at 2:50 PM, Nick Pentreath <[email protected]> 
> wrote:
>> @Robert sorry for the delay in responding, I was away on vacation.
>>
>> Here's a link to a gist of a very simple implementation of parallelized SGD
>> using Spark (https://gist.github.com/4707012). It basically replicates the
>> existing Spark logistic regression example, but using sklearn's linear_model
>> module. However the approach used is iterative parameter mixtures (where the
>> local weight vectors are averaged and the resulting weight vector
>> rebroadcast) as opposed to distributed gradient descent (where the local
>> gradients are aggregated, a gradient step taken on the master and the weight
>> vector rebroadcast) - see
>> http://faculty.utpa.edu/reillycf/courses/CSCI6175-F11/papers/nips2010mannetal.pdf
>> for some details.
>
> Very cool. Thanks!
>
> --
> Robert Kern
>
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-- 
Peter Prettenhofer

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