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On the Complexity of Clustering with Relaxed Size Constraints
[chapter]
2016
Lecture Notes in Computer Science
We study the computational complexity of the problem of computing an optimal clustering {A1, A2, ..., A k } of a set of points assuming that every cluster size |Ai| belongs to a given set M of positive integers. We present a polynomial time algorithm for solving the problem in dimension 1, i.e. when the points are simply rational values, for an arbitrary set M of size constraints, which extends to the 1-norm an analogous procedure known for the 2-norm. Moreover, we prove that in the Euclidean
doi:10.1007/978-3-319-41168-2_3
fatcat:g4uouolskzaqtds2ccl4tefwiy