Published In

Theory of Computing Systems

Document Type

Article

Publication Date

7-2023

Subjects

Parameterized approximation -- Kernelization

Abstract

In this work, we study the k-median clustering problem with an additional equal-size constraint on the clusters from the perspective of parameterized preprocessing. Our main result is the first lossy (2-approximate) polynomial kernel for this problem parameterized by the cost of clustering. We complement this result by establishing lower bounds for the problem that eliminate the existence of an (exact) kernel of polynomial size and a PTAS.

Rights

Copyright (c) 2023 The Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

DOI

10.1007/s00224-023-10129-9

Persistent Identifier

https://archives.pdx.edu/ds/psu/40648

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