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> (Apparently determining if knots are trivial is NP. This doesn’t bode well for neural networks.) Yes it doesn't, but what do I know (not much). Another annoy
by 0xdeadbeefbabe 11y ago
> (Apparently determining if knots are trivial is NP. This doesn’t bode well for neural networks.)
Yes it doesn't, but what do I know (not much). Another annoying property of NN is knowing when they are fully baked.
Edit: Yet they have clearly grown in popularity over the past year. Does that imply anything about the "determining if knots are trivial is NP" criticism? Or does it just mean they are popular for other reasons such as their appeal to people who love black boxes?
- Houshalter 11y agoI don't really see the relevance. As the article itself says, you can just add more dimensions and separating the clusters becomes trivial. And empirically underfitting and local optima do not seem to be big issues for large neural networks.