Learning Reduced Order Dynamics via Geometric Representations
Imran Nasim, Melanie Weber
SCML 2024
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.
Imran Nasim, Melanie Weber
SCML 2024
Liya Fan, Fa Zhang, et al.
JPDC
Els van Herreweghen, Uta Wille
USENIX Workshop on Smartcard Technology 1999
Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence