Haskell Neural Network

[Alp Mestanogullari]

Hi,

Actually, the project has been pretty dead for a while. I have been quite
busy and the others too I guess.
Last time we talked about the project, we wanted to go in two directions:

- I've always found that it was pretty reasonable to have a special
representation (using vectors and matrices) for feed-forward neural
networks, so I wanted (and still do) some day to rewrite HNN using the
'vector' package, probably together with hmatrix I guess, using all the
performance tricks I have learned since I started Haskell.

- There were a few other people interested in writing a more general neural
networks framework, thus graph-based, so that they would be able to
experiment with much more complicated models (like real-time feedback for
general neural networks, etc).

I may actually have some time for rewriting a good and viable feed-forward
implementation. But definitely not the latter.

Would you be interested in somehow contributing ?

On Fri, Jan 13, 2012 at 7:35 PM, Kiet Lam <ktklam9 at gmail.com> wrote:

> Hey, I don't know how active the HNN project is, but after looking at your
> code draft, I have a few suggestions.
>
> You guys are making it way too hard on yourselves by going to a graph
> representation.
> This will no doubt have a performance impact and will / already has
> introduced needless complexity to your codes.
>
> From the Wiki page of HNN, it seems like you are interested in a
> feed-forward neural network. From this,
> I suggest that you take a step back and go to a vector/matrix
> representation.
>
> This will reduces a lot of the complexity in your codes.
>
> Moreover, many of the advanced training algorithms (Conjugate Gradient,
> BFGS, L-BFGS) requires the representation
> of the weight parameters to be in vector form. If the HNN project
> continues to use a graph representation,
> it would be costly to convert back-and-forth from graph to vector to use
> the advance training algorithms.
>
> I understand that you guys want to make the most general representation
> possible so the project would be scalable, but I think
> it would behoove you guys to re-evaluate your representation of the neural
> network.
>
> Thanks.
>
> Kiet Lam
>
> _______________________________________________
> Hnn mailing list
> Hnn at projects.haskell.org
> http://projects.haskell.org/cgi-bin/mailman/listinfo/hnn
>
>


-- 
Alp Mestanogullari
http://alpmestan.wordpress.com/
http://alp.developpez.com/
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