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arXiv · 2312.07628

Finding a Cluster in Incomplete Data

Eduard Eiben·Robert Ganian·Iyad Kanj·Sebastian Ordyniak·Stefan Szeider
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Abstract

We study two variants of the fundamental problem of finding a cluster in incomplete data. In the problems under consideration, we are given a multiset of incomplete $d$-dimensional vectors over the binary domain and integers $k$ and $r$, and the goal is to complete the missing vector entries so that the multiset of complete vectors either contains (i) a cluster of $k$ vectors of radius at most $r$, or (ii) a cluster of $k$ vectors of diameter at most $r$. We give tight characterizations of the parameterized complexity of the problems under consideration with respect to the parameters $k$, $r$, and a third parameter that captures the missing vector entries.

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Eduard Eiben, Robert Ganian, Iyad Kanj, Sebastian Ordyniak, Stefan Szeider. 2023-12-12. Finding a Cluster in Incomplete Data. https://arxiv.org/abs/2312.07628

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