[Computer-go] Move Evaluation in Go Using Deep Convolutional Neural Networks

Álvaro Begué alvaro.begue at gmail.com
Thu Dec 25 04:41:50 PST 2014


You are going to be computing gradients of functions, and most people find
it easier to think about these things using a type that roughly corresponds
to the notion of real number. You can use a fixed-point representation of
reals, which uses ints in the end, but then you have to worry about what
scale to use, so you get enough precision but you don't run the risk of
overflowing.

The only reason I might consider a fixed-point representation is to achieve
reproducibility of results.




On Thu, Dec 25, 2014 at 5:44 AM, hughperkins2 <hughperkins2 at gmail.com>
wrote:

> > as I want to by graphic card for CNN: do I need double precision
> performance?
>
> Personally, i was thinking of experimenting with ints, bytes, and shorts,
> even less precise than singles :-)
>
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