madhadron
Joined 14 years ago
Joined 14 years ago
You don't need sequences of independent samples for assignment. You need sequences that are independent of the sequence of subjects being assigned. If you have a very small number of possible sequences then you can't get independence by the pigeon hole principle, but both 2^(64*N) (from N random 64 bit numbers) or 2^64 - 1 (for N samples from a PRNG) are so large that it doesn't matter.
The argument about a sample of seeds not producing a flat histogram is also weird. Of course it doesn't. That's irrelevant to whether uniformly sampling a sequence of N 64 bit numbers from the space the PRNG provides produces independent sequences from the subjects.
Perhaps this is part of it? Tens of thousands of lines of code seems like a very small repo to me.
> they are still fighting over what 'Hwaet' means
I don't think anyone is particularly fighting over what it means, just how to translate it when there isn't a parallel in modern English. My personal favorite is a translation that opens with 'Bro!'.
That's hilarious! You might want to add a bit more transition for the joke before the other points above, though.
The next big jumps were to collections of functions not parameterized by subsets of R^n. Wavelets use a tree shapes parameter space.
There’s a whole, interesting area of overcomplete basis sets that I have been meaning to look into where you give up your basis functions being orthogonal and all those nice properties in exchange for having multiple options for adapting better to different signal characteristics.
I don’t think these transforms are going to be relevant to understanding neural nets, though. They are, by their nature, doing something with nonlinear structures in high dimensions which are not smoothly extended across their domain, which is the opposite problem all our current approaches to functional analysis deal with.