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Fractal Dimension and Lower Bounds for Geometric Problems
2018
International Symposium on Computational Geometry
We study the complexity of geometric problems on spaces of low fractal dimension. It was recently shown by [Sidiropoulos & Sridhar, SoCG 2017] that several problems admit improved solutions when the input is a pointset in Euclidean space with fractal dimension smaller than the ambient dimension. In this paper we prove nearly-matching lower bounds, thus establishing nearly-optimal bounds for various problems as a function of the fractal dimension. More specifically, we show that for any set of n
doi:10.4230/lipics.socg.2018.70
dblp:conf/compgeom/SidiropoulosSS18
fatcat:2va63efjubd5ld2qk7qu2v7xay