Hi Deb,

On Tue, Feb 25, 2014 at 7:07 AM, Debasish Das <debasish.da...@gmail.com> wrote:
> Continuation on last email sent by mistake:
>
> Is cpl license is compatible with apache ?
>
> http://opensource.org/licenses/cpl1.0.php

Based on what I read here, there is no problem to include CPL code in
apache project
as long as the code isn't modified, and we include the maven binary.
https://www.apache.org/legal/3party.html

> Mallet jars are available on maven. They have hessian based solvers which
> looked interesting along with bfgs and cg.

We found that hessian based solvers don't scale as the # of features grow, and
we have lots of customers trying to train sparse input. That's our motivation to
work on L-BFGS which approximate hessian using just a few vectors.

Just take a look at MALLET, and it does have L-BFGS and its variant OWL-QN
which can tackle L1 problem. Since implementing L-BFGS is very subtle, I don't
know the quality of the mallet implementation. Personally, I
implemented one based
on textbook, and not very stable. If MALLET is robust, I'll go for it
since it has more
features, and already in maven.

> Note that right now the version is not blas optimized. With jblas or
> netlib-java discussions that's going on it can be improved. Also it runs on
> a single thread which can be improved...so there is scope for further
> improvements in the code.

I think it will not impact performance even it's not blas optimized
nor multi-threaded,
since most of the parallelization is in computing gradientSum and
lossSum in Spark,
and the optimizer just takes gradientSum, lossSum, and weights to get
the newWeights.

As a result, 99.9% of time is in computing gradientSum and lossSum.
Only small amount
of time is in optimization.

>
> Basically Xiangrui, is there a push back on making optimizers part of spark
> mllib ? I am exploring cg and qp solvers for spark mllib as well and I am
> developing these as part of mllib optimization. I was hoping we should be
> able to publish mllib as a maven artifact later.
>
> Thanks.
> Deb

Thanks.

Sincerely,

DB Tsai
Machine Learning Engineer
Alpine Data Labs
--------------------------------------
Web: http://alpinenow.com/

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