Fast, Exact Nearest Neighbor in Arbitrary Dimensions with a Cover Tree
published: Feb. 25, 2007, recorded: August 2004, views: 2008
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Given only a metric between points, how quickly can the nearest neighbor of a point be found? In the worst case, this time is O(n). When these points happen to obey a dimensionality constraint, more speed is possible.
The "cover tree" is O(n) space datastructure which allows us to answer queries in O(log(n)) time given a fixed intrinsic dimensionality. It is also a very practical algorithm yielding speedups between a factor of 1 and 1000 on all datasets tested.
This speedup has direct implications for several learning algorithms, simulations, and some systems
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