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arxiv: 1003.5874 · v1 · submitted 2010-03-30 · 💻 cs.CG

Stability of epsilon-Kernels

classification 💻 cs.CG
keywords eps-kernelsizealgorithmpointsthereeveryfactorfloor
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Given a set P of n points in |R^d, an eps-kernel K subset P approximates the directional width of P in every direction within a relative (1-eps) factor. In this paper we study the stability of eps-kernels under dynamic insertion and deletion of points to P and by changing the approximation factor eps. In the first case, we say an algorithm for dynamically maintaining a eps-kernel is stable if at most O(1) points change in K as one point is inserted or deleted from P. We describe an algorithm to maintain an eps-kernel of size O(1/eps^{(d-1)/2}) in O(1/eps^{(d-1)/2} + log n) time per update. Not only does our algorithm maintain a stable eps-kernel, its update time is faster than any known algorithm that maintains an eps-kernel of size O(1/eps^{(d-1)/2}). Next, we show that if there is an eps-kernel of P of size k, which may be dramatically less than O(1/eps^{(d-1)/2}), then there is an (eps/2)-kernel of P of size O(min {1/eps^{(d-1)/2}, k^{floor(d/2)} log^{d-2} (1/eps)}). Moreover, there exists a point set P in |R^d and a parameter eps > 0 such that if every eps-kernel of P has size at least k, then any (eps/2)-kernel of P has size Omega(k^{floor(d/2)}).

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