Erik Altman, Jovan Blanusa, et al.
NeurIPS 2023
In this paper, we shall show the following experimental results: (1) the one-dimensional clustering algorithm advocated by Slagle and Lee(1) can be generalized to the n-dimensional case, n > 1: (2) if a set of points in some n-space (n > 1) are linearly ordered through the short spanning path algorithm, then this set of points can be considered as occupying a one-dimensional space and the original n-dimensional clustering problem can now be viewed as a one-dimensional clustering problem; (3) a short spanning path usually contains as much information as a minimal spanning tree; (4) the one-dimensional clustering algorithm can be used to find the long links in a short spanning path or a minimal spanning tree. These long links have to be broken to obtain clusters. © 1974.
Erik Altman, Jovan Blanusa, et al.
NeurIPS 2023
John R. Kender, Rick Kjeldsen
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ryan Johnson, Ippokratis Pandis
CIDR 2013
Hannah Kim, Celia Cintas, et al.
IJCAI 2023