# Balanced k-Center Clustering When k Is A Constant

arXiv: https://arxiv.org/abs/1704.02515 · HTML: https://mlsanity.com/paper/1704.02515/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Apr 2017.

## Built on by (most cited first, 1 of 1)

- [Tight FPT Approximation for Constrained k-Center and k-Supplier](https://mlsanity.com/paper/2110.14242/) (2021)

## Abstract (arXiv)

The problem of constrained k-center clustering has attracted significant attention in the past decades. In this paper, we study balanced k-center cluster where the size of each cluster is constrained by the given lower and upper bounds. The problem is motivated by the applications in processing and analyzing large-scale data in high dimension. We provide a simple nearly linear time 4-approximation algorithm when the number of clusters k is assumed to be a constant. Comparing with existing method, our algorithm improves the approximation ratio and significantly reduces the time complexity. Moreover, our result can be easily extended to any metric space.