Non-Uniform $k$-Center and Greedy Clustering
Tanmay Inamdar, Kasturi Varadarajan

TL;DR
This paper presents an $O(1)$-approximation algorithm for the Non-Uniform $k$-Center problem with four distinct radii types, advancing the understanding of non-uniform clustering problems and their relation to the $k$-center literature.
Contribution
It introduces a novel approach combining techniques from $k$-center to achieve a constant approximation for 4-radius types in the non-uniform $k$-center problem.
Findings
Achieved an $O(1)$-approximation for 4-radius types.
Linked non-uniform $k$-center with colorful $k$-center problems.
Demonstrated the potential for further progress on the CGK conjecture.
Abstract
In the Non-Uniform -Center problem, a generalization of the famous -center clustering problem, we want to cover the given set of points in a metric space by finding a placement of balls with specified radii. In -NUC Problem, we assume that the number of distinct radii is equal to , and we are allowed to use balls of radius , for . This problem was introduced by Chakrabarty et al. [ACM Trans. Alg. 16(4):46:1-46:19], who showed that a constant approximation for -NUC is not possible if is unbounded. On the other hand, they gave a bicriteria approximation that violates the number of allowed balls as well as the given radii by a constant factor. They also conjectured that a constant approximation for -NUC should be possible if is a fixed constant. Since then, there has been steady progress towards resolving this conjecture --…
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