[Noisebridge-discuss] Build advice for a new system / heavy cluster GPU AI processing?

Mike Schachter mike at mindmech.com
Tue Jul 12 15:10:30 PDT 2011

On Tue, Jul 12, 2011 at 6:21 AM, Sai <sai at saizai.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).

Cool! Assuming you're using 8 different directions, at some point you
may consider using a number between 1-360 for the direction and
solve a regression problem instead. I wonder if that would hurt/help...

>> 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:
>> http://svmlight.joachims.org/svm_multiclass.html
> 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?

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