[Noisebridge-discuss] Build advice for a new system / heavy cluster GPU AI processing?
sai at saizai.com
Tue Jul 12 06:21:03 PDT 2011
On Mon, Jul 11, 2011 at 23:22, Mike Schachter <mike at mindmech.com> wrote:
> Sounds reasonable - are you deailng with spike data, or something
> like EEG?
Primate motor cortex spike data together with timings of direction
cue, go cue, and start of movement. Need to predict movement direction
based on ±1s from direction cue (before the go).
> You have to retrain from scratch per hyperparam combo,
Not just hyperparam combo, but nuisance param combos too (for the grid
search). That's the part that kills me.
> libsvm uses "one-vs-one" multi-class classification. That means,
> per hyperparam combo, for 8 classes it's training something like
> (8 choose 2) / 2 = 14 independent SVMs to do it. You might want
> to look into SVM-lite for multi-class classification:
Hm. How is it better?
In particular, would it be better than eg the sigmoid-only
CUDA-enabled libsvm variants I pointed to in the OP, if I got a
beefier nVidia card to use?
> I'm most familiar with the random forests in R:
Sounds like I have some reading to do. :-)
> Definitely try random forests, they're the hot shit and people will
> eat it up. Comparing things to linear classifiers (or SVMs with a
> linear kernel) is kind of classic.
I also just want to learn more on machine learning while I'm at it…
> If you want to never finish your PhD
… but FWIW this is actually bonus work for one class in my MA that's
(Hence why I said "within a month".)
> keep going and try out neural networks, deep nets (neural
> networks with many pre-trained hidden layers),
… buuut I did say I'd like to learn more stuff. :-P
Also I do think that this could be turned into a legit paper etc.,
which would be fun. ;-)
> And more importantly, there is a python framework called Theano
> which takes care of parallelizing things on the GPU for you:
Ooo. I'm guessing that requires me coding the thing from scratch
though, which is probably outside of what I can plausibly do in the
Thanks for all the pointers!
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