

Ask HN: Any real uses of Neural Networks? - TeMPOraL

I'm struggling to find any use case for neural networks, where they wouldn't be existing solutions that are better and more manageable. Any ideas where and in what context neural networks are actually useful?
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milliams
They're extensively used in particle physics as a method of performing multi-
variate selections of data. It's a common case that we have a large data set
which contains the signal we're looking for. Each entry in the data set will
have a large number of variables, some of which will provide some
discriminating power between our signal and background. By training a neural
network to use those variables to tell the difference between signal and
background we can extract the maximum efficiency from our data.

Of course we could use any other multi-variate method (boosted-decision trees
are popular) but neural networks are becoming more and more common.

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_delirium
They're a reasonable supervised learning technique. I don't prefer them
myself, but they have some advantages for online learning and low memory
requirements, among other things, and do decently in supervised-learning-
roundup benchmarks (e.g.
[http://www.cs.pitt.edu/~litman/courses/cs2710/papers/empiric...](http://www.cs.pitt.edu/~litman/courses/cs2710/papers/empirical.icml06.pdf)).
Of the older supervised-learning techniques (before SVMs/boosting/etc.), they
tend to do better than alternatives such as decision trees (though decision
trees are more interpretable).

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canopylabs
While this is more anecdotal, I know quite a few financial firms use neural
networks for their stock trading algorithms. It's less about whether or not
they're the right tool, and a matter of using every tool there is to see what
happens to work best. Here's a very brief example:
<http://www.i2r.org/nnstocks.pdf>

Also, often times these methods are combined to get even better results. See
"ensemble learning: <http://en.wikipedia.org/wiki/Ensemble_learning>

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hbhanu
I used growing neural gas (
[http://web.cs.swarthmore.edu/~meeden/DevelopmentalRobotics/f...](http://web.cs.swarthmore.edu/~meeden/DevelopmentalRobotics/fritzke95.pdf)
) for my MS research dealing with keystroke dynamics (specifically, modeling
Hidden Markov Models on interkey-delays to identify a user's language). When
you have a large set of data and you need to identify exemplars for that data,
it does a pretty good job. As _delirium said, though, it requires a degree of
supervision and tweaking to get growth parameters, etc.

Edit: I use 'supervision' in a 'it might take a few tries to get it working
ideally' sense, not a 'you need a priori knowledge of the data' sense.

