Intuition question. You draw two vectors from an n-dimensional isotropic Gaussian where n>>1. What is the typical angle between them?
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2/ If you do not know it, learn it. Be it because yo want to understand DL models with many weights or brain circuits with many neurons, you will need an intuition for the properties of high dimensional spaces.
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3/ And you do not need to be a mathematician. I am not - I am just a physicist. But enough of a scientist to know that whether a `fact' is true is not decide by voting!!!
- Još 3 druga odgovora
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I assume most of my readers would go through the distribution of dot product path. Or do you mean how to derive the ab=||a||||b||cos \theta equation in the first place?
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The mean dot product is zero and that fact is trivial. The next question would be whether you expect concentration of measure.
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norms grow linearly with n. variance of sum of independent variables also grows linearly with n. And there is your concentration of measure.
- Još 1 odgovor
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Basic concentration inequalities give not just the proof but bounds on how close you get to pi/2 for finite sized spaces :)
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I would tip around the idea of inner product and its relation to the angle of two random vectors, and what happens when the dimension increases. Fix the first one to [1,0,0,0...] if you like... :)
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