Nice On Mar 31, 2016 7:48 AM, "Álvaro Begué" <alvaro.be...@gmail.com> wrote:
> A very simple-minded way of trying to identify what a particular neuron in > the upper layers is doing is to find the 50 positions in the database that > make it produce the highest activation values. If the neuron is in one of > the convolutional layers, you get a full 19x19 image of activation values, > which would let you figure out what particular local pattern it seems to be > detecting. If the neuron is in a fully-connected layer at the end, you only > get one overall value, but you could still try to compute the gradient of > its activation with respect to all the inputs, and that would tell you > something about what parts of the board led to this activation being high. > I think this would be a fun exercise, and you'll probably be able to > understand something about at least some of the neurons. > > Álvaro. > > > > On Thu, Mar 31, 2016 at 9:55 AM, Michael Markefka < > michael.marke...@gmail.com> wrote: > >> Then again DNNs also manage feature extraction on unlabeled data with >> increasing levels of abstraction towards upper layers. Perhaps one >> could apply such a specifically trained DNN to artificial board >> situations that emphasize specific concepts and examine the network's >> activation, trying to map activation patterns to human Go concepts. >> >> Still hard work, and questionable payoff, but just wanted to pitch >> that in as idea. >> >> >> > However, if someone was to do all the dirty work setting up all the >> > infrastructure, hunt down the training data and then financially >> facilitate >> > the thousands of hours of human work and the tens to hundreds of >> thousands >> > of hours of automated learning work, I would become substantially more >> > interested...and think a high quality desired outcome remains a low >> > probability. >> _______________________________________________ >> Computer-go mailing list >> Computer-go@computer-go.org >> http://computer-go.org/mailman/listinfo/computer-go >> > > > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go >
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