Correlation Clustering with Constrained Cluster Sizes and Extended Weights Bounds
Machine Learning
2015-05-25 v3 Data Structures and Algorithms
Abstract
We consider the problem of correlation clustering on graphs with constraints on both the cluster sizes and the positive and negative weights of edges. Our contributions are twofold: First, we introduce the problem of correlation clustering with bounded cluster sizes. Second, we extend the regime of weight values for which the clustering may be performed with constant approximation guarantees in polynomial time and apply the results to the bounded cluster size problem.
Keywords
Cite
@article{arxiv.1411.0547,
title = {Correlation Clustering with Constrained Cluster Sizes and Extended Weights Bounds},
author = {Gregory J. Puleo and Olgica Milenkovic},
journal= {arXiv preprint arXiv:1411.0547},
year = {2015}
}
Comments
17 pages, simplified the last section and fixed some other minor errors