Work

Lossy Kernelization of Same-Size Clustering

Year: 2021
Type: preprint
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 existences of an (exact) kernel of polynomial size and a PTAS.
Language: English
Open Access status: green
OpenAlex ID: W4287075884
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