4 ms·
And if you think sufficiently hard about curved knifes and cherries on high-dimensional pies, you end up studying machine learning theory (https://en.wikipedia.
by cscheid 4y ago
And if you think sufficiently hard about curved knifes and cherries on high-dimensional pies, you end up studying machine learning theory (https://en.wikipedia.org/wiki/Vapnik%E2%80%93Chervonenkis_dimension https://en.wikipedia.org/wiki/Vapnik%E2%80%93Chervonenkis_di...)
- TeMPOraL 4y agoIf you're implying that any problem of N-dimensional geometry can be reduced to machine learning techniques, then maybe there is a way to reinterpret machine learning as cutting N-dimensional cakes with M-dimensional knives?
- knodi123 4y agoOf course. There's a trivial proof that all neural networks can be reduced to a sufficiently complicated cake scenario. It's called Turing's Birthday Party.
- cscheid 4y agoNot _any_ problem, but the _specific_ problem of determining how many arbitrarily placed points (cherries) can be split by a given shape of hypothesis classes/classifiers (knives) is literally the definition of VC-dimension, yes :)