Geometric applications of a randomized optimization technique

@inproceedings{Chan1998GeometricAO,
title={Geometric applications of a randomized optimization technique},
author={Timothy M. Chan},
booktitle={SCG '98},
year={1998}
}

We propose a simple, general, randomized technique to reduce certain geo- metric optimization problems to their corresponding decision problems. These reductions increase the expected time complexity by only a constant factor and eliminate extra log- arithmic factors in previous, often more complicated, deterministic approaches (such as parametric searching). Faster algorithms are thus obtained for a variety of problems in computational geometry: finding minimal k-point subsets, matching pointâ€¦Â Expand

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and M

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