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It's been a four month dry spell, but new blog post! Linear Fit Search A search algorithm competitive with binary search, but having different properties. https://blog.demofox.org/2019/03/22/linear-fit-search/ …pic.twitter.com/r8zL7Ln82s
This makes me wonder about a few things. First, would this sort of search be good for ranged searches? Ie, for a random set of 50 numbers between 0 and 99, return al values between 40 and 60 (as begin/end indices).
My natural next thought is wondering if/how this might work in higher dimensions (if you consider your examples to be 1D). Is there an analogous structure in those higher dimensions that lets me find all objects in an AABB overlap?
And more importantly, could such a structure be worthwhile, from a performance standpoint?
I like this range idea if you guess wrong for the min, it might be useful info for the max. Cool idea.
And i think if going quadratic or cubic, there'd be even more opportunities for information sharing.
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