Our starting point is the observation that randomization is often confined to repeated random sampling over a fixed domain.
Abstract: A number of efficient probabilistic algorithms based on the combination of divide-and-conquer and random sampling have been recently discovered.
Abstract: The combination of divide-and-conquer and random sampling has proven very effective in the design of fast geometric algorithms.
Feb 27, 1989 · The combination of divide-and-conquer and random sampling has proven very effective in the design of fast geometric algorithms.
The combination of divide-and conquer and random sampling has proven very effective in the design of fast geometric algorithms. A flurry of effcient ...
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A number of efficient probabilistic algorithms based on the combination of divide-and-conquer and random sampling have been recently discovered.
The basic idea is to pick a random subset R of r hyperplanes and argue that, with high probability, each simplex of any triangulation T of R intersects O(n(logr)/ ...
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Our methods also extend to the parallelization of various algorithms in computational geometry that rely upon the random sampling technique of Clarkson. Finally ...
B. Chazelle and J. Friedman. A deterministic view of random sampling and its use in computational geometry. InProceedings of the 29th Annual IEEE Symposium on ...