Dynamic Generalized Closest Pair: Revisiting Eppstein's Technique
Author(s) -
Timothy M. Chan
Publication year - 2019
Publication title -
society for industrial and applied mathematics ebooks
Language(s) - English
Resource type - Book series
DOI - 10.1137/1.9781611976014.6
Subject(s) - logarithm , transformation (genetics) , mathematics , simple (philosophy) , combinatorics , constant (computer programming) , data structure , function (biology) , k nearest neighbors algorithm , amortized analysis , algorithm , discrete mathematics , computer science , mathematical analysis , artificial intelligence , biochemistry , gene , epistemology , philosophy , evolutionary biology , programming language , chemistry , biology
Eppstein (1995) gave a technique to transform any data structure for dynamic nearest neighbor queries into a data structure for dynamic closest pair, for any distance function; the transformation increases the time bound by two logarithmic factors. We present a similar, simple transformation that is just as good, and can avoid the extra logarithmic factors when the query and update time of the given structure exceed n for some constant ε > 0. Consequently, in the case of an arbitrary distance function, we obtain an optimal O(n)-space data structure to maintain the dynamic closest pair of n points in O(n) amortized time plus O(n) distance evaluations per update.
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