Practical and efficient geometric "-approximations
Robert Marini · 2006
We adapt an algorithm for computing a deterministic sample in a set system to compute ! - approximations for certain geometric set systems. We give algorithms to evaluate the quality of our samples. Our implementation shows that our de- terministic samples, although more costly to ob- tain, significantly outperform random samples in quality. These implementations may have utility in computer graphics and statistics.