[R-sig-hpc] Optimizer Question

[Suzen, Mehmet]

Hi Hesen,

I am not sure if the premise "..ecosystem-wise they are better than
using R packages..". First of all almost all of the optimisation
techniques as far as I know in (deep) machine learning are the
gradient base. R provides superb ecosystem for gradient free
optimisation and other constraint based optimisations where Keras or
tensorflow solves. Yes, they scale better in Gradient decent base
algorithms but they don't cover the spectrum R ecosystem provides, at
least not as of today.  Have a look at the spectrum of optimisations R
ecosystem provides:
https://cran.r-project.org/web/views/Optimization.html
It is pretty diverse.

Cheers,
-m




On 5 August 2017 at 23:12, Hesen Peng <hesen.peng at gmail.com> wrote:
> I apologize since this answer is kind of off topic. If you look beyond the
> boundary, TensorFlow and Theano have been very popular these days in the
> deep learning field and they can be used to solve optimization problems.
> They are being used to solve problems involving millions of parameters. And
> I do thing ecosystem-wise they are better than using R packages.
>
>
>
>
> On Fri, Aug 4, 2017 at 1:45 PM, Bromaghin, Jeffrey <jbromaghin at usgs.gov>
> wrote:
>
>> My apologies!  The structure is close to linear, but there is a scaling so
>> that modeled proportions sum to 1.0, so the problem is nonlinear.  There
>> are quite a few linear constraints as all parameters are non-negative and
>> subsets of the
>> parameters must sum to 1.
>>
>> Best regards,
>> Jeff
>>
>> -----------------------------------------------
>> Jeffrey F. Bromaghin, PhD
>> Research Statistician
>> USGS Alaska Science Center
>> Marine Ecosystems Office
>> 4210 University Drive
>> Anchorage, AK 99508
>> 907-786-7086
>> jbromaghin at usgs.gov
>> *http://alaska.usgs.gov/science/biology/quantitative_ecology/index.php
>> <http://alaska.usgs.gov/science/biology/quantitative_ecology/index.php>*
>>
>> On Fri, Aug 4, 2017 at 12:35 PM, Roger Koenker <rkoenker at illinois.edu>
>> wrote:
>>
>> > You don’t say anything about the nature of your problem domain beyond its
>> > size,
>> > but for convex problems Mosek is a good option, and there is an R
>> interface
>> > called Rmosek that is quite convenient.
>> >
>> > url:    www.econ.uiuc.edu/~roger            Roger Koenker
>> > email    rkoenker at uiuc.edu            Department of Economics
>> > vox:     217-333-4558                University of Illinois
>> > fax:       217-244-6678                Urbana, IL 61801
>> >
>> > > On Aug 4, 2017, at 3:21 PM, Bromaghin, Jeffrey <jbromaghin at usgs.gov>
>> > wrote:
>> > >
>> > > Dear r-sig-hpc members,
>> > >
>> > > I have developed a new method of interest to ecologists that involves
>> > > solving a large optimization problem.  One example I used in a recent
>> > paper
>> > > had over 5,700 parameters.  I have been using Matlab and a optimization
>> > > library called Tomlab, which works quite well.  However, I would like
>> to
>> > > incorporate this new method into an R package, but question whether the
>> > > optimizers available in R can handle a problem of this size
>> efficiently.
>> > > Does anyone have experience solving such large problems with any of the
>> > > optimizers available in R and, if so, what optimizer(s) would you
>> > recommend
>> > > I try?
>> > >
>> > > Thank you,
>> > > Jeff
>> > > -----------------------------------------------
>> > > Jeffrey F. Bromaghin, PhD
>> > > Research Statistician
>> > > USGS Alaska Science Center
>> > > Marine Ecosystems Office
>> > > 4210 University Drive
>> > > Anchorage, AK 99508
>> > > 907-786-7086
>> > > jbromaghin at usgs.gov
>> > > *http://alaska.usgs.gov/science/biology/quantitative_ecology/index.php
>> > > <http://alaska.usgs.gov/science/biology/quantitative_ecology/index.php
>> >*
>> > >
>> > >       [[alternative HTML version deleted]]
>> > >
>> > > _______________________________________________
>> > > R-sig-hpc mailing list
>> > > R-sig-hpc at r-project.org
>> > > https://stat.ethz.ch/mailman/listinfo/r-sig-hpc
>> >
>> >
>> >
>>
>>         [[alternative HTML version deleted]]
>>
>> _______________________________________________
>> R-sig-hpc mailing list
>> R-sig-hpc at r-project.org
>> https://stat.ethz.ch/mailman/listinfo/r-sig-hpc
>>
>
>
>
> --
> Hesen Peng 彭河森
>
>         [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-hpc mailing list
> R-sig-hpc at r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-hpc