Fast way to compute the minimal distance of two sets of k-dimensional vectors
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Published on 2010-06-06T13:30:23Z
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2010/06/06
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I two sets of k-dimensional vectors, where k is around 500 and the number of vectors is usually smaller. I want to compute the (arbitrarily defined) minimal distance between the two sets. A naive approach would be this:
(loop for a in set1
for b in set2
minimizing (distance a b))
However, this requires O(n² * distance) computations. Is there a faster way of doing this?
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