We present an O((m + n)√n log n) time algorithm to select the k th smallest item from an m × n totally monotone matrix for any k ≤ ran. This is the first subquadratic algorithm for selecting an item from a totally monotone matrix. Our method also yields an algorithm for generalized row selection in monotone matrices of the same time complexity. Given a set S = {p1, …, pn} of n points in convex position and a vector k = {k1, …, kn}, we also present an O(n4/3 logO(1) n) algorithm to compute the kith nearest neighbor of pi for every i ≤ n; c is an appropriate constant. This algorithm is considerably faster than the one based on a row-selection algorithm for monotone matrices. If the points of S are arbitrary, then the kith h nearest neighbor of pi, for all i ≤ n, can be computed in time O(n7/5 logc n), which also improves upon the previously best-known result.
CITATION STYLE
Agarwal, P. K., & Sen, S. (1994). Selection in monotone matrices and computing kth nearest neighbors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 824 LNCS, pp. 13–24). Springer Verlag. https://doi.org/10.1007/3-540-58218-5_2
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