Finding a Cluster in Incomplete Data
Data Structures and Algorithms
2023-12-14 v1
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 -dimensional vectors over the binary domain and integers and , and the goal is to complete the missing vector entries so that the multiset of complete vectors either contains (i) a cluster of vectors of radius at most , or (ii) a cluster of vectors of diameter at most . We give tight characterizations of the parameterized complexity of the problems under consideration with respect to the parameters , , and a third parameter that captures the missing vector entries.
Keywords
Cite
@article{arxiv.2312.07628,
title = {Finding a Cluster in Incomplete Data},
author = {Eduard Eiben and Robert Ganian and Iyad Kanj and Sebastian Ordyniak and Stefan Szeider},
journal= {arXiv preprint arXiv:2312.07628},
year = {2023}
}
Comments
Short version appeared at ESA 2022. arXiv admin note: substantial text overlap with arXiv:1911.01465