New Complexity and Algorithmic Bounds for Minimum Consistent Subsets
Aritra Banik, Sayani Das, Anil Maheshwari, Bubai Manna, Subhas C Nandy, Krishna Priya K M, Bodhayan Roy, Sasanka Roy, Abhishek Sahu

TL;DR
This paper investigates the computational complexity of the Minimum Consistent Subset (MCS) problem, establishing NP-completeness for trees and interval graphs, and providing a fixed-parameter tractable algorithm for trees with improved efficiency.
Contribution
It proves NP-completeness of MCS on trees with the number of colors as a parameter, and introduces a more efficient FPT algorithm, also extending complexity results to interval graphs.
Findings
NP-complete for trees with color parameter
FPT algorithm with $O(2^{6c}n^6)$ time complexity
NP-complete for interval graphs
Abstract
In the Minimum Consistent Subset (MCS) problem, we are presented with a connected simple undirected graph , consisting of a vertex set of size and an edge set . Each vertex in is assigned a color from the set . The objective is to determine a subset with minimum possible cardinality, such that for every vertex , at least one of its nearest neighbors in (measured in terms of the hop distance) shares the same color as . A variant of MCS is the minimum strict consistent subset (MSCS) in which instead of requiring at least one nearest neighbor of , all the nearest neighbors of in must have the same color as . The decision version for MCS problem as well as for MSCS problem asks whether there exists a subset of cardinality at most for some positive integer . The MCS problem is known to be…
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