11,639 research outputs found

    Squarepants in a Tree: Sum of Subtree Clustering and Hyperbolic Pants Decomposition

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    We provide efficient constant factor approximation algorithms for the problems of finding a hierarchical clustering of a point set in any metric space, minimizing the sum of minimimum spanning tree lengths within each cluster, and in the hyperbolic or Euclidean planes, minimizing the sum of cluster perimeters. Our algorithms for the hyperbolic and Euclidean planes can also be used to provide a pants decomposition, that is, a set of disjoint simple closed curves partitioning the plane minus the input points into subsets with exactly three boundary components, with approximately minimum total length. In the Euclidean case, these curves are squares; in the hyperbolic case, they combine our Euclidean square pants decomposition with our tree clustering method for general metric spaces.Comment: 22 pages, 14 figures. This version replaces the proof of what is now Lemma 5.2, as the previous proof was erroneou

    Essential Constraints of Edge-Constrained Proximity Graphs

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    Given a plane forest F=(V,E)F = (V, E) of V=n|V| = n points, we find the minimum set SES \subseteq E of edges such that the edge-constrained minimum spanning tree over the set VV of vertices and the set SS of constraints contains FF. We present an O(nlogn)O(n \log n )-time algorithm that solves this problem. We generalize this to other proximity graphs in the constraint setting, such as the relative neighbourhood graph, Gabriel graph, β\beta-skeleton and Delaunay triangulation. We present an algorithm that identifies the minimum set SES\subseteq E of edges of a given plane graph I=(V,E)I=(V,E) such that ICGβ(V,S)I \subseteq CG_\beta(V, S) for 1β21 \leq \beta \leq 2, where CGβ(V,S)CG_\beta(V, S) is the constraint β\beta-skeleton over the set VV of vertices and the set SS of constraints. The running time of our algorithm is O(n)O(n), provided that the constrained Delaunay triangulation of II is given.Comment: 24 pages, 22 figures. A preliminary version of this paper appeared in the Proceedings of 27th International Workshop, IWOCA 2016, Helsinki, Finland. It was published by Springer in the Lecture Notes in Computer Science (LNCS) serie

    Generalized gamma approximation with rates for urns, walks and trees

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    We study a new class of time inhomogeneous P\'olya-type urn schemes and give optimal rates of convergence for the distribution of the properly scaled number of balls of a given color to nearly the full class of generalized gamma distributions with integer parameters, a class which includes the Rayleigh, half-normal and gamma distributions. Our main tool is Stein's method combined with characterizing the generalized gamma limiting distributions as fixed points of distributional transformations related to the equilibrium distributional transformation from renewal theory. We identify special cases of these urn models in recursive constructions of random walk paths and trees, yielding rates of convergence for local time and height statistics of simple random walk paths, as well as for the size of random subtrees of uniformly random binary and plane trees.Comment: Published at http://dx.doi.org/10.1214/15-AOP1010 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org
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