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Adaptive sampling for geometric problems over data streams
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Subgradient and sampling algorithms for l1 regression
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Adaptive sampling for geometric problems over data streams
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Theoretical Computer Science
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Computational Geometry: Theory and Applications
Data structures for range-aggregate extent queries
Computational Geometry: Theory and Applications
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We present a general technique for approximating various descriptors of the extent of a set P of n points in Rd when the dimension d is an arbitrary fixed constant. For a given extent measure μ and a parameter ϵ 0, it computes in time O(n + 1/ϵO(1)) a subset Q ⊆ P of size 1/ϵO(1), with the property that (1 − ϵ)μ(P) ≤ μ(Q) ≤ μ(P). The specific applications of our technique include ϵ-approximation algorithms for (i) computing diameter, width, and smallest bounding box, ball, and cylinder of P, (ii) maintaining all the previous measures for a set of moving points, and (iii) fitting spheres and cylinders through a point set P. Our algorithms are considerably simpler, and faster in many cases, than previously known algorithms.